EasyPlatform fix-ci

[Implementation] Analyze Github Actions logs and fix issues

install

source · Clone the upstream repo

git clone https://github.com/duc01226/EasyPlatform

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/duc01226/EasyPlatform "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills/fix-ci" ~/.claude/skills/duc01226-easyplatform-fix-ci && rm -rf "$T"

manifest: .claude/skills/fix-ci/SKILL.md

source content

[IMPORTANT] Use
TaskCreate
to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

AI Mistake Prevention — Failure modes to avoid on every task:

Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal.

Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing.

Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain.

Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path.

When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site.

Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code.

Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks.

Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis.

Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly.

Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Understand Code First — HARD-GATE: Do NOT write, plan, or fix until you READ existing code.
Search 3+ similar patterns (
grep
/
glob
) — cite
file:line
evidence
Read existing files in target area — understand structure, base classes, conventions
Run
python .claude/scripts/code_graph trace <file> --direction both --json
when
.code-graph/graph.db
exists
Map dependencies via
connections
or
callers_of
— know what depends on your target
Write investigation to
.ai/workspace/analysis/
for non-trivial tasks (3+ files)
Re-read analysis file before implementing — never work from memory alone

NEVER invent new patterns when existing ones work — match exactly or document deviation
BLOCKED until:
- [ ]
Read target files
- [ ]
Grep 3+ patterns
- [ ]
Graph trace (if graph.db exists)
- [ ]
Assumptions verified with evidence

Evidence-Based Reasoning — Speculation is FORBIDDEN. Every claim needs proof.
Cite
file:line
, grep results, or framework docs for EVERY claim
Declare confidence: >80% act freely, 60-80% verify first, <60% DO NOT recommend

Cross-service validation required for architectural changes

"I don't have enough evidence" is valid and expected output
BLOCKED until:
- [ ]
Evidence file path (
file:line
)
- [ ]
Grep search performed
- [ ]
3+ similar patterns found
- [ ]
Confidence level stated

Forbidden without proof: "obviously", "I think", "should be", "probably", "this is because" If incomplete → output:
"Insufficient evidence. Verified: [...]. Not verified: [...]."

```
docs/project-reference/domain-entities-reference.md
```
— Domain entity catalog, relationships, cross-service sync (read when task involves business entities/models) (content auto-injected by hook — check for [Injected: ...] header before reading)

Estimation — Modified Fibonacci: 1(trivial) → 2(small) → 3(medium) → 5(large) → 8(very large) → 13(epic, SHOULD split) → 21(MUST ATTENTION split). Output
story_points
and
complexity
in plan frontmatter. Complexity auto-derived: 1-2=Low, 3-5=Medium, 8=High, 13+=Critical.

Skill Variant: Variant of
/fix
— specialized for CI/GitHub Actions log analysis.

Quick Summary

Goal: Analyze GitHub Actions CI logs to identify and fix build/test failures in the pipeline.

Workflow:

Fetch — Download CI logs from GitHub Actions
Analyze — Identify root cause from log output (build errors, test failures, env issues)
Fix — Apply targeted fix based on traced root cause

Key Rules:

Infrastructure Context: Read
```
docs/project-config.json
```
→
```
infrastructure.cicd.tool
```
to identify CI platform (e.g., "azure-devops", "github-actions", "gitlab-ci"). Target the correct pipeline config files for that platform.
Debug Mindset: every claim needs
```
file:line
```
evidence
Focus on CI-specific issues (env vars, Docker, dependencies, build order)
Verify fix doesn't break local development

Root Cause Debugging — Systematic approach, never guess-and-check.
Reproduce — Confirm the issue exists with evidence (error message, stack trace, screenshot)

Isolate — Narrow to specific file/function/line using binary search + graph trace

Trace — Follow data flow from input to failure point. Read actual code, don't infer.

Hypothesize — Form theory with confidence %. State what evidence supports/contradicts it

Verify — Test hypothesis with targeted grep/read. One variable at a time.
Fix — Address root cause, not symptoms. Verify fix doesn't break callers via graph
connections
NEVER: Guess without evidence. Fix symptoms instead of cause. Skip reproduction step.

Debug Mindset (NON-NEGOTIABLE)

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Do NOT assume the first hypothesis is correct — verify with actual code traces
Every root cause claim must include
```
file:line
```
evidence
If you cannot prove a root cause with a code trace, state "hypothesis, not confirmed"
Question assumptions: "Is this really the cause?" → trace the actual execution path
Challenge completeness: "Are there other contributing factors?" → check related code paths
No "should fix it" without proof — verify the fix addresses the traced root cause

⚠️ MANDATORY: Confidence & Evidence Gate

MANDATORY IMPORTANT MUST ATTENTION declare

Confidence: X%

with evidence list +

file:line

proof for EVERY claim. 95%+ recommend freely | 80-94% with caveats | 60-79% list unknowns | <60% STOP — gather more evidence.

Github Actions URL

<url>$ARGUMENTS</url>

⚠️ Validate Before Fix (NON-NEGOTIABLE): After CI log analysis + root cause identification, MUST ATTENTION present findings + proposed fix to user via
AskUserQuestion
and get explicit approval BEFORE any code changes. No silent fixes.

Workflow

Use
```
debugger
```
subagent to read the github actions logs with
```
gh
```
command, analyze and find the root cause of the issues and report back to main agent. 1.5. Write analysis findings to
```
.ai/workspace/analysis/{ci-issue}.analysis.md
```
. Re-read before implementing fix.
🛑 Present root cause + proposed fix →
AskUserQuestion
→ wait for user approval.
Start implementing the fix based the reports and solutions.
Use
```
tester
```
agent to test the fix and make sure it works, then report back to main agent.
If there are issues or failed tests, repeat from step 2.
After finishing, respond back to user with a summary of the changes and explain everything briefly, guide user to get started and suggest the next steps.

Notes

If
```
gh
```
command is not available, instruct the user to install and authorize GitHub CLI first.
After fixing, MUST ATTENTION run
```
/prove-fix
```
— build code proof traces per change with confidence scores. Never skip.

Closing Reminders

IMPORTANT MUST ATTENTION break work into small todo tasks using
```
TaskCreate
```
BEFORE starting
IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
IMPORTANT MUST ATTENTION cite
```
file:line
```
evidence for every claim (confidence >80% to act)
IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
IMPORTANT MUST ATTENTION STOP after 3 failed fix attempts — report outcomes, ask user before #4 MANDATORY IMPORTANT MUST ATTENTION READ the following files before starting:
IMPORTANT MUST ATTENTION search 3+ existing patterns and read code BEFORE any modification. Run graph trace when graph.db exists.
IMPORTANT MUST ATTENTION cite
```
file:line
```
evidence for every claim. Confidence >80% to act, <60% = do NOT recommend.
IMPORTANT MUST ATTENTION include
```
story_points
```
and
```
complexity
```
in plan frontmatter. SP > 8 = split.
MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.
MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.