Paperclip create-agent-adapter

install
source · Clone the upstream repo
git clone https://github.com/paperclipai/paperclip
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/paperclipai/paperclip "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.agents/skills/create-agent-adapter" ~/.claude/skills/paperclipai-paperclip-create-agent-adapter && rm -rf "$T"
manifest: .agents/skills/create-agent-adapter/SKILL.md
source content

Creating a Paperclip Agent Adapter

An adapter bridges Paperclip's orchestration layer to a specific AI agent runtime (Claude Code, Codex CLI, a custom process, an HTTP endpoint, etc.). Each adapter is a self-contained package that provides implementations for three consumers: the server, the UI, and the CLI.


1. Architecture Overview

packages/adapters/<name>/
  src/
    index.ts            # Shared metadata (type, label, models, agentConfigurationDoc)
    server/
      index.ts          # Server exports: execute, sessionCodec, parse helpers
      execute.ts        # Core execution logic (AdapterExecutionContext -> AdapterExecutionResult)
      parse.ts          # Stdout/result parsing for the agent's output format
    ui/
      index.ts          # UI exports: parseStdoutLine, buildConfig
      parse-stdout.ts   # Line-by-line stdout -> TranscriptEntry[] for the run viewer
      build-config.ts   # CreateConfigValues -> adapterConfig JSON for agent creation form
    cli/
      index.ts          # CLI exports: formatStdoutEvent
      format-event.ts   # Colored terminal output for `paperclipai run --watch`
  package.json
  tsconfig.json

Three separate registries consume adapter modules:

RegistryLocationInterface
Server
server/src/adapters/registry.ts
ServerAdapterModule
UI
ui/src/adapters/registry.ts
UIAdapterModule
CLI
cli/src/adapters/registry.ts
CLIAdapterModule

2. Shared Types (
@paperclipai/adapter-utils
)

All adapter interfaces live in

packages/adapter-utils/src/types.ts
. Import from
@paperclipai/adapter-utils
(types) or
@paperclipai/adapter-utils/server-utils
(runtime helpers).

Core Interfaces

// The execute function signature — every adapter must implement this
interface AdapterExecutionContext {
  runId: string;
  agent: AdapterAgent;          // { id, companyId, name, adapterType, adapterConfig }
  runtime: AdapterRuntime;      // { sessionId, sessionParams, sessionDisplayId, taskKey }
  config: Record<string, unknown>;  // The agent's adapterConfig blob
  context: Record<string, unknown>; // Runtime context (taskId, wakeReason, approvalId, etc.)
  onLog: (stream: "stdout" | "stderr", chunk: string) => Promise<void>;
  onMeta?: (meta: AdapterInvocationMeta) => Promise<void>;
  authToken?: string;
}

interface AdapterExecutionResult {
  exitCode: number | null;
  signal: string | null;
  timedOut: boolean;
  errorMessage?: string | null;
  usage?: UsageSummary;           // { inputTokens, outputTokens, cachedInputTokens? }
  sessionId?: string | null;      // Legacy — prefer sessionParams
  sessionParams?: Record<string, unknown> | null;  // Opaque session state persisted between runs
  sessionDisplayId?: string | null;
  provider?: string | null;       // "anthropic", "openai", etc.
  model?: string | null;
  costUsd?: number | null;
  resultJson?: Record<string, unknown> | null;
  summary?: string | null;        // Human-readable summary of what the agent did
  clearSession?: boolean;         // true = tell Paperclip to forget the stored session
}

interface AdapterSessionCodec {
  deserialize(raw: unknown): Record<string, unknown> | null;
  serialize(params: Record<string, unknown> | null): Record<string, unknown> | null;
  getDisplayId?(params: Record<string, unknown> | null): string | null;
}

Module Interfaces

// Server — registered in server/src/adapters/registry.ts
interface ServerAdapterModule {
  type: string;
  execute(ctx: AdapterExecutionContext): Promise<AdapterExecutionResult>;
  testEnvironment(ctx: AdapterEnvironmentTestContext): Promise<AdapterEnvironmentTestResult>;
  sessionCodec?: AdapterSessionCodec;
  supportsLocalAgentJwt?: boolean;
  models?: { id: string; label: string }[];
  agentConfigurationDoc?: string;
}

// UI — registered in ui/src/adapters/registry.ts
interface UIAdapterModule {
  type: string;
  label: string;
  parseStdoutLine: (line: string, ts: string) => TranscriptEntry[];
  ConfigFields: ComponentType<AdapterConfigFieldsProps>;
  buildAdapterConfig: (values: CreateConfigValues) => Record<string, unknown>;
}

// CLI — registered in cli/src/adapters/registry.ts
interface CLIAdapterModule {
  type: string;
  formatStdoutEvent: (line: string, debug: boolean) => void;
}

2.1 Adapter Environment Test Contract

Every server adapter must implement

testEnvironment(...)
. This powers the board UI "Test environment" button in agent configuration.

type AdapterEnvironmentCheckLevel = "info" | "warn" | "error";
type AdapterEnvironmentTestStatus = "pass" | "warn" | "fail";

interface AdapterEnvironmentCheck {
  code: string;
  level: AdapterEnvironmentCheckLevel;
  message: string;
  detail?: string | null;
  hint?: string | null;
}

interface AdapterEnvironmentTestResult {
  adapterType: string;
  status: AdapterEnvironmentTestStatus;
  checks: AdapterEnvironmentCheck[];
  testedAt: string; // ISO timestamp
}

interface AdapterEnvironmentTestContext {
  companyId: string;
  adapterType: string;
  config: Record<string, unknown>; // runtime-resolved adapterConfig
}

Guidelines:

  • Return structured diagnostics, never throw for expected findings.
  • Use
    error
    for invalid/unusable runtime setup (bad cwd, missing command, invalid URL).
  • Use
    warn
    for non-blocking but important situations.
  • Use
    info
    for successful checks and context.

Severity policy is product-critical: warnings are not save blockers.
Example: for

claude_local
, detected
ANTHROPIC_API_KEY
must be a
warn
, not an
error
, because Claude can still run (it just uses API-key auth instead of subscription auth).


3. Step-by-Step: Creating a New Adapter

3.1 Create the Package

packages/adapters/<name>/
  package.json
  tsconfig.json
  src/
    index.ts
    server/index.ts
    server/execute.ts
    server/parse.ts
    ui/index.ts
    ui/parse-stdout.ts
    ui/build-config.ts
    cli/index.ts
    cli/format-event.ts

package.json — must use the four-export convention:

{
  "name": "@paperclipai/adapter-<name>",
  "version": "0.0.1",
  "private": true,
  "type": "module",
  "exports": {
    ".": "./src/index.ts",
    "./server": "./src/server/index.ts",
    "./ui": "./src/ui/index.ts",
    "./cli": "./src/cli/index.ts"
  },
  "dependencies": {
    "@paperclipai/adapter-utils": "workspace:*",
    "picocolors": "^1.1.1"
  },
  "devDependencies": {
    "typescript": "^5.7.3"
  }
}

3.2 Root
index.ts
— Adapter Metadata

This file is imported by all three consumers (server, UI, CLI). Keep it dependency-free (no Node APIs, no React).

export const type = "my_agent";        // snake_case, globally unique
export const label = "My Agent (local)";

export const models = [
  { id: "model-a", label: "Model A" },
  { id: "model-b", label: "Model B" },
];

export const agentConfigurationDoc = `# my_agent agent configuration
...document all config fields here...
`;

Required exports:

  • type
    — the adapter type key, stored in
    agents.adapter_type
  • label
    — human-readable name for the UI
  • models
    — available model options for the agent creation form
  • agentConfigurationDoc
    — markdown describing all
    adapterConfig
    fields (used by LLM agents configuring other agents)

Writing

agentConfigurationDoc
as routing logic:

The

agentConfigurationDoc
is read by LLM agents (including Paperclip agents that create other agents). Write it as routing logic, not marketing copy. Include concrete "use when" and "don't use when" guidance so an LLM can decide whether this adapter is appropriate for a given task.

export const agentConfigurationDoc = `# my_agent agent configuration

Adapter: my_agent

Use when:
- The agent needs to run MyAgent CLI locally on the host machine
- You need session persistence across runs (MyAgent supports thread resumption)
- The task requires MyAgent-specific tools (e.g. web search, code execution)

Don't use when:
- You need a simple one-shot script execution (use the "process" adapter instead)
- The agent doesn't need conversational context between runs (process adapter is simpler)
- MyAgent CLI is not installed on the host

Core fields:
- cwd (string, required): absolute working directory for the agent process
...
`;

Adding explicit negative cases improves adapter selection accuracy. One concrete anti-pattern is worth more than three paragraphs of description.

3.3 Server Module

server/execute.ts
— The Core

This is the most important file. It receives an

AdapterExecutionContext
and must return an
AdapterExecutionResult
.

Required behavior:

  1. Read config — extract typed values from
    ctx.config
    using helpers (
    asString
    ,
    asNumber
    ,
    asBoolean
    ,
    asStringArray
    ,
    parseObject
    from
    @paperclipai/adapter-utils/server-utils
    )
  2. Build environment — call
    buildPaperclipEnv(agent)
    then layer in
    PAPERCLIP_RUN_ID
    , context vars (
    PAPERCLIP_TASK_ID
    ,
    PAPERCLIP_WAKE_REASON
    ,
    PAPERCLIP_WAKE_COMMENT_ID
    ,
    PAPERCLIP_APPROVAL_ID
    ,
    PAPERCLIP_APPROVAL_STATUS
    ,
    PAPERCLIP_LINKED_ISSUE_IDS
    ), user env overrides, and auth token
  3. Resolve session — check
    runtime.sessionParams
    /
    runtime.sessionId
    for an existing session; validate it's compatible (e.g. same cwd); decide whether to resume or start fresh
  4. Render prompt — use
    renderTemplate(template, data)
    with the template variables:
    agentId
    ,
    companyId
    ,
    runId
    ,
    company
    ,
    agent
    ,
    run
    ,
    context
  5. Call onMeta — emit adapter invocation metadata before spawning the process
  6. Spawn the process — use
    runChildProcess()
    for CLI-based agents or
    fetch()
    for HTTP-based agents
  7. Parse output — convert the agent's stdout into structured data (session id, usage, summary, errors)
  8. Handle session errors — if resume fails with "unknown session", retry with a fresh session and set
    clearSession: true
  9. Return AdapterExecutionResult — populate all fields the agent runtime supports

Environment variables the server always injects:

VariableSource
PAPERCLIP_AGENT_ID
agent.id
PAPERCLIP_COMPANY_ID
agent.companyId
PAPERCLIP_API_URL
Server's own URL
PAPERCLIP_RUN_ID
Current run id
PAPERCLIP_TASK_ID
context.taskId
or
context.issueId
PAPERCLIP_WAKE_REASON
context.wakeReason
PAPERCLIP_WAKE_COMMENT_ID
context.wakeCommentId
or
context.commentId
PAPERCLIP_APPROVAL_ID
context.approvalId
PAPERCLIP_APPROVAL_STATUS
context.approvalStatus
PAPERCLIP_LINKED_ISSUE_IDS
context.issueIds
(comma-separated)
PAPERCLIP_API_KEY
authToken
(if no explicit key in config)

server/parse.ts
— Output Parser

Parse the agent's stdout format into structured data. Must handle:

  • Session identification — extract session/thread ID from init events
  • Usage tracking — extract token counts (input, output, cached)
  • Cost tracking — extract cost if available
  • Summary extraction — pull the agent's final text response
  • Error detection — identify error states, extract error messages
  • Unknown session detection — export an
    is<Agent>UnknownSessionError()
    function for retry logic

Treat agent output as untrusted. The stdout you're parsing comes from an LLM-driven process that may have executed arbitrary tool calls, fetched external content, or been influenced by prompt injection in the files it read. Parse defensively:

  • Never
    eval()
    or dynamically execute anything from output
  • Use safe extraction helpers (
    asString
    ,
    asNumber
    ,
    parseJson
    ) — they return fallbacks on unexpected types
  • Validate session IDs and other structured data before passing them through
  • If output contains URLs, file paths, or commands, do not act on them in the adapter — just record them

server/index.ts
— Server Exports

export { execute } from "./execute.js";
export { testEnvironment } from "./test.js";
export { parseMyAgentOutput, isMyAgentUnknownSessionError } from "./parse.js";

// Session codec — required for session persistence
export const sessionCodec: AdapterSessionCodec = {
  deserialize(raw) { /* raw DB JSON -> typed params or null */ },
  serialize(params) { /* typed params -> JSON for DB storage */ },
  getDisplayId(params) { /* -> human-readable session id string */ },
};

server/test.ts
— Environment Diagnostics

Implement adapter-specific preflight checks used by the UI test button.

Minimum expectations:

  1. Validate required config primitives (paths, commands, URLs, auth assumptions)
  2. Return check objects with deterministic
    code
    values
  3. Map severity consistently (
    info
    /
    warn
    /
    error
    )
  4. Compute final status:
    • fail
      if any
      error
    • warn
      if no errors and at least one warning
    • pass
      otherwise

This operation should be lightweight and side-effect free.

3.4 UI Module

ui/parse-stdout.ts
— Transcript Parser

Converts individual stdout lines into

TranscriptEntry[]
for the run detail viewer. Must handle the agent's streaming output format and produce entries of these kinds:

  • init
    — model/session initialization
  • assistant
    — agent text responses
  • thinking
    — agent thinking/reasoning (if supported)
  • tool_call
    — tool invocations with name and input
  • tool_result
    — tool results with content and error flag
  • user
    — user messages in the conversation
  • result
    — final result with usage stats
  • stdout
    — fallback for unparseable lines
export function parseMyAgentStdoutLine(line: string, ts: string): TranscriptEntry[] {
  // Parse JSON line, map to appropriate TranscriptEntry kind(s)
  // Return [{ kind: "stdout", ts, text: line }] as fallback
}

ui/build-config.ts
— Config Builder

Converts the UI form's

CreateConfigValues
into the
adapterConfig
JSON blob stored on the agent.

export function buildMyAgentConfig(v: CreateConfigValues): Record<string, unknown> {
  const ac: Record<string, unknown> = {};
  if (v.cwd) ac.cwd = v.cwd;
  if (v.promptTemplate) ac.promptTemplate = v.promptTemplate;
  if (v.model) ac.model = v.model;
  ac.timeoutSec = 0;
  ac.graceSec = 15;
  // ... adapter-specific fields
  return ac;
}

UI Config Fields Component

Create

ui/src/adapters/<name>/config-fields.tsx
with a React component implementing
AdapterConfigFieldsProps
. This renders adapter-specific form fields in the agent creation/edit form.

Use the shared primitives from

ui/src/components/agent-config-primitives
:

  • Field
    — labeled form field wrapper
  • ToggleField
    — boolean toggle with label and hint
  • DraftInput
    — text input with draft/commit behavior
  • DraftNumberInput
    — number input with draft/commit behavior
  • help
    — standard hint text for common fields

The component must support both

create
mode (using
values
/
set
) and
edit
mode (using
config
/
eff
/
mark
).

3.5 CLI Module

cli/format-event.ts
— Terminal Formatter

Pretty-prints stdout lines for

paperclipai run --watch
. Use
picocolors
for coloring.

import pc from "picocolors";

export function printMyAgentStreamEvent(raw: string, debug: boolean): void {
  // Parse JSON line from agent stdout
  // Print colored output: blue for system, green for assistant, yellow for tools
  // In debug mode, print unrecognized lines in gray
}

4. Registration Checklist

After creating the adapter package, register it in all three consumers:

4.1 Server Registry (
server/src/adapters/registry.ts
)

import { execute as myExecute, sessionCodec as mySessionCodec } from "@paperclipai/adapter-my-agent/server";
import { agentConfigurationDoc as myDoc, models as myModels } from "@paperclipai/adapter-my-agent";

const myAgentAdapter: ServerAdapterModule = {
  type: "my_agent",
  execute: myExecute,
  sessionCodec: mySessionCodec,
  models: myModels,
  supportsLocalAgentJwt: true,  // true if agent can use Paperclip API
  agentConfigurationDoc: myDoc,
};

// Add to the adaptersByType map
const adaptersByType = new Map<string, ServerAdapterModule>(
  [..., myAgentAdapter].map((a) => [a.type, a]),
);

4.2 UI Registry (
ui/src/adapters/registry.ts
)

import { myAgentUIAdapter } from "./my-agent";

const adaptersByType = new Map<string, UIAdapterModule>(
  [..., myAgentUIAdapter].map((a) => [a.type, a]),
);

With

ui/src/adapters/my-agent/index.ts
:

import type { UIAdapterModule } from "../types";
import { parseMyAgentStdoutLine } from "@paperclipai/adapter-my-agent/ui";
import { MyAgentConfigFields } from "./config-fields";
import { buildMyAgentConfig } from "@paperclipai/adapter-my-agent/ui";

export const myAgentUIAdapter: UIAdapterModule = {
  type: "my_agent",
  label: "My Agent",
  parseStdoutLine: parseMyAgentStdoutLine,
  ConfigFields: MyAgentConfigFields,
  buildAdapterConfig: buildMyAgentConfig,
};

4.3 CLI Registry (
cli/src/adapters/registry.ts
)

import { printMyAgentStreamEvent } from "@paperclipai/adapter-my-agent/cli";

const myAgentCLIAdapter: CLIAdapterModule = {
  type: "my_agent",
  formatStdoutEvent: printMyAgentStreamEvent,
};

// Add to the adaptersByType map

5. Session Management — Designing for Long Runs

Sessions allow agents to maintain conversation context across runs. The system is codec-based — each adapter defines how to serialize/deserialize its session state.

Design for long runs from the start. Treat session reuse as the default primitive, not an optimization to add later. An agent working on an issue may be woken dozens of times — for the initial assignment, approval callbacks, re-assignments, manual nudges. Each wake should resume the existing conversation so the agent retains full context about what it has already done, what files it has read, and what decisions it has made. Starting fresh each time wastes tokens on re-reading the same files and risks contradictory decisions.

Key concepts:

  • sessionParams
    is an opaque
    Record<string, unknown>
    stored in the DB per task
  • The adapter's
    sessionCodec.serialize()
    converts execution result data to storable params
  • sessionCodec.deserialize()
    converts stored params back for the next run
  • sessionCodec.getDisplayId()
    extracts a human-readable session ID for the UI
  • cwd-aware resume: if the session was created in a different cwd than the current config, skip resuming (prevents cross-project session contamination)
  • Unknown session retry: if resume fails with a "session not found" error, retry with a fresh session and return
    clearSession: true
    so Paperclip wipes the stale session

If the agent runtime supports any form of context compaction or conversation compression (e.g. Claude Code's automatic context management, or Codex's

previous_response_id
chaining), lean on it. Adapters that support session resume get compaction for free — the agent runtime handles context window management internally across resumes.

Pattern (from both claude-local and codex-local):

const canResumeSession =
  runtimeSessionId.length > 0 &&
  (runtimeSessionCwd.length === 0 || path.resolve(runtimeSessionCwd) === path.resolve(cwd));
const sessionId = canResumeSession ? runtimeSessionId : null;

// ... run attempt ...

// If resume failed with unknown session, retry fresh
if (sessionId && !proc.timedOut && exitCode !== 0 && isUnknownSessionError(output)) {
  const retry = await runAttempt(null);
  return toResult(retry, { clearSessionOnMissingSession: true });
}

6. Server-Utils Helpers

Import from

@paperclipai/adapter-utils/server-utils
:

HelperPurpose
asString(val, fallback)
Safe string extraction
asNumber(val, fallback)
Safe number extraction
asBoolean(val, fallback)
Safe boolean extraction
asStringArray(val)
Safe string array extraction
parseObject(val)
Safe
Record<string, unknown>
extraction
parseJson(str)
Safe JSON.parse returning
Record
or null
renderTemplate(tmpl, data)
{{path.to.value}}
template rendering
buildPaperclipEnv(agent)
Standard
PAPERCLIP_*
env vars
redactEnvForLogs(env)
Redact sensitive keys for onMeta
ensureAbsoluteDirectory(cwd)
Validate cwd exists and is absolute
ensureCommandResolvable(cmd, cwd, env)
Validate command is in PATH
ensurePathInEnv(env)
Ensure PATH exists in env
runChildProcess(runId, cmd, args, opts)
Spawn with timeout, logging, capture

7. Conventions and Patterns

Naming

  • Adapter type:
    snake_case
    (e.g.
    claude_local
    ,
    codex_local
    )
  • Package name:
    @paperclipai/adapter-<kebab-name>
  • Package directory:
    packages/adapters/<kebab-name>/

Config Parsing

  • Never trust
    config
    values directly — always use
    asString
    ,
    asNumber
    , etc.
  • Provide sensible defaults for every optional field
  • Document all fields in
    agentConfigurationDoc

Prompt Templates

  • Support
    promptTemplate
    for every run
  • Use
    renderTemplate()
    with the standard variable set
  • Default prompt should use
    DEFAULT_PAPERCLIP_AGENT_PROMPT_TEMPLATE
    from
    @paperclipai/adapter-utils/server-utils
    so local adapters share Paperclip's execution contract: act in the same heartbeat, avoid planning-only exits unless requested, leave durable progress and a next action, use child issues instead of polling, mark blockers with owner/action, and respect governance boundaries.

Error Handling

  • Differentiate timeout vs process error vs parse failure
  • Always populate
    errorMessage
    on failure
  • Include raw stdout/stderr in
    resultJson
    when parsing fails
  • Handle the agent CLI not being installed (command not found)

Logging

  • Call
    onLog("stdout", ...)
    and
    onLog("stderr", ...)
    for all process output — this feeds the real-time run viewer
  • Call
    onMeta(...)
    before spawning to record invocation details
  • Use
    redactEnvForLogs()
    when including env in meta

Paperclip Skills Injection

Paperclip ships shared skills (in the repo's top-level

skills/
directory) that agents need at runtime — things like the
paperclip
API skill and the
paperclip-create-agent
workflow skill. Each adapter is responsible for making these skills discoverable by its agent runtime without polluting the agent's working directory.

The constraint: never copy or symlink skills into the agent's

cwd
. The cwd is the user's project checkout — writing
.claude/skills/
or any other files into it would contaminate the repo with Paperclip internals, break git status, and potentially leak into commits.

The pattern: create a clean, isolated location for skills and tell the agent runtime to look there.

How claude-local does it:

  1. At execution time, create a fresh tmpdir:
    mkdtemp("paperclip-skills-")
  2. Inside it, create
    .claude/skills/
    (the directory structure Claude Code expects)
  3. Symlink each skill directory from the repo's
    skills/
    into the tmpdir's
    .claude/skills/
  4. Pass the tmpdir to Claude Code via
    --add-dir <tmpdir>
    — this makes Claude Code discover the skills as if they were registered in that directory, without touching the agent's actual cwd
  5. Clean up the tmpdir in a
    finally
    block after the run completes
// From claude-local execute.ts
async function buildSkillsDir(): Promise<string> {
  const tmp = await fs.mkdtemp(path.join(os.tmpdir(), "paperclip-skills-"));
  const target = path.join(tmp, ".claude", "skills");
  await fs.mkdir(target, { recursive: true });
  const entries = await fs.readdir(PAPERCLIP_SKILLS_DIR, { withFileTypes: true });
  for (const entry of entries) {
    if (entry.isDirectory()) {
      await fs.symlink(
        path.join(PAPERCLIP_SKILLS_DIR, entry.name),
        path.join(target, entry.name),
      );
    }
  }
  return tmp;
}

// In execute(): pass --add-dir to Claude Code
const skillsDir = await buildSkillsDir();
args.push("--add-dir", skillsDir);
// ... run process ...
// In finally: fs.rm(skillsDir, { recursive: true, force: true })

How codex-local does it:

Codex has a global personal skills directory (

$CODEX_HOME/skills
or
~/.codex/skills
). The adapter symlinks Paperclip skills there if they don't already exist. This is acceptable because it's the agent tool's own config directory, not the user's project.

// From codex-local execute.ts
async function ensureCodexSkillsInjected(onLog) {
  const skillsHome = path.join(codexHomeDir(), "skills");
  await fs.mkdir(skillsHome, { recursive: true });
  for (const entry of entries) {
    const target = path.join(skillsHome, entry.name);
    const existing = await fs.lstat(target).catch(() => null);
    if (existing) continue;  // Don't overwrite user's own skills
    await fs.symlink(source, target);
  }
}

For a new adapter: figure out how your agent runtime discovers skills/plugins, then choose the cleanest injection path:

  1. Best: tmpdir + flag (like claude-local) — if the runtime supports an "additional directory" flag, create a tmpdir, symlink skills in, pass the flag, clean up after. Zero side effects.
  2. Acceptable: global config dir (like codex-local) — if the runtime has a global skills/plugins directory separate from the project, symlink there. Skip existing entries to avoid overwriting user customizations.
  3. Acceptable: env var — if the runtime reads a skills/plugin path from an environment variable, point it at the repo's
    skills/
    directory directly.
  4. Last resort: prompt injection — if the runtime has no plugin system, include skill content in the prompt template itself. This uses tokens but avoids filesystem side effects entirely.

Skills as loaded procedures, not prompt bloat. The Paperclip skills (like

paperclip
and
paperclip-create-agent
) are designed as on-demand procedures: the agent sees skill metadata (name + description) in its context, but only loads the full SKILL.md content when it decides to invoke a skill. This keeps the base prompt small. When writing
agentConfigurationDoc
or prompt templates for your adapter, do not inline skill content — let the agent runtime's skill discovery do the work. The descriptions in each SKILL.md frontmatter act as routing logic: they tell the agent when to load the full skill, not what the skill contains.

Explicit vs. fuzzy skill invocation. For production workflows where reliability matters (e.g. an agent that must always call the Paperclip API to report status), use explicit instructions in the prompt template: "Use the paperclip skill to report your progress." Fuzzy routing (letting the model decide based on description matching) is fine for exploratory tasks but unreliable for mandatory procedures.


8. Security Considerations

Adapters sit at the boundary between Paperclip's orchestration layer and arbitrary agent execution. This is a high-risk surface.

Treat Agent Output as Untrusted

The agent process runs LLM-driven code that reads external files, fetches URLs, and executes tools. Its output may be influenced by prompt injection from the content it processes. The adapter's parse layer is a trust boundary — validate everything, execute nothing.

Secret Injection via Environment, Not Prompts

Never put secrets (API keys, tokens) into prompt templates or config fields that flow through the LLM. Instead, inject them as environment variables that the agent's tools can read directly:

  • PAPERCLIP_API_KEY
    is injected by the server into the process environment, not the prompt
  • User-provided secrets in
    config.env
    are passed as env vars, redacted in
    onMeta
    logs
  • The
    redactEnvForLogs()
    helper automatically masks any key matching
    /(key|token|secret|password|authorization|cookie)/i

This follows the "sidecar injection" pattern: the model never sees the real secret value, but the tools it invokes can read it from the environment.

Network Access

If your agent runtime supports network access controls (sandboxing, allowlists), configure them in the adapter:

  • Prefer minimal allowlists over open internet access. An agent that only needs to call the Paperclip API and GitHub should not have access to arbitrary hosts.
  • Skills + network = amplified risk. A skill that teaches the agent to make HTTP requests combined with unrestricted network access creates an exfiltration path. Constrain one or the other.
  • If the runtime supports layered policies (org-level defaults + per-request overrides), wire the org-level policy into the adapter config and let per-agent config narrow further.

Process Isolation

  • CLI-based adapters inherit the server's user permissions. The
    cwd
    and
    env
    config determine what the agent process can access on the filesystem.
  • dangerouslySkipPermissions
    /
    dangerouslyBypassApprovalsAndSandbox
    flags exist for development convenience but must be documented as dangerous in
    agentConfigurationDoc
    . Production deployments should not use them.
  • Timeout and grace period (
    timeoutSec
    ,
    graceSec
    ) are safety rails — always enforce them. A runaway agent process without a timeout can consume unbounded resources.

9. TranscriptEntry Kinds Reference

The UI run viewer displays these entry kinds:

KindFieldsUsage
init
model
,
sessionId
Agent initialization
assistant
text
Agent text response
thinking
text
Agent reasoning/thinking
user
text
User message
tool_call
name
,
input
Tool invocation
tool_result
toolUseId
,
content
,
isError
Tool result
result
text
,
inputTokens
,
outputTokens
,
cachedTokens
,
costUsd
,
subtype
,
isError
,
errors
Final result with usage
stderr
text
Stderr output
system
text
System messages
stdout
text
Raw stdout fallback

10. Testing

Create tests in

server/src/__tests__/<adapter-name>-adapter.test.ts
. Test:

  1. Output parsing — feed sample stdout through your parser, verify structured output
  2. Unknown session detection — verify the
    is<Agent>UnknownSessionError
    function
  3. Config building — verify
    buildConfig
    produces correct adapterConfig from form values
  4. Session codec — verify serialize/deserialize round-trips

11. Minimal Adapter Checklist

  • packages/adapters/<name>/package.json
    with four exports (
    .
    ,
    ./server
    ,
    ./ui
    ,
    ./cli
    )
  • Root
    index.ts
    with
    type
    ,
    label
    ,
    models
    ,
    agentConfigurationDoc
  • server/execute.ts
    implementing
    AdapterExecutionContext -> AdapterExecutionResult
  • server/test.ts
    implementing
    AdapterEnvironmentTestContext -> AdapterEnvironmentTestResult
  • server/parse.ts
    with output parser and unknown-session detector
  • server/index.ts
    exporting
    execute
    ,
    testEnvironment
    ,
    sessionCodec
    , parse helpers
  • ui/parse-stdout.ts
    with
    StdoutLineParser
    for the run viewer
  • ui/build-config.ts
    with
    CreateConfigValues -> adapterConfig
    builder
  • ui/src/adapters/<name>/config-fields.tsx
    React component for agent form
  • ui/src/adapters/<name>/index.ts
    assembling the
    UIAdapterModule
  • cli/format-event.ts
    with terminal formatter
  • cli/index.ts
    exporting the formatter
  • Registered in
    server/src/adapters/registry.ts
  • Registered in
    ui/src/adapters/registry.ts
  • Registered in
    cli/src/adapters/registry.ts
  • Added to workspace in root
    pnpm-workspace.yaml
    (if not already covered by glob)
  • Tests for parsing, session codec, and config building