Conduct Empirical Wire Capture

Set up a reproducible wire-capture harness for a CLI tool's outbound HTTP and telemetry, matching each observability target to the cheapest channel that captures it.

Scope and Ethics

Read this before configuring any capture.

• Wire capture is for your own requests against your own account, on your own machine. Capturing other users' traffic is exfiltration, not research, and is out of scope.
• Credentials almost always appear in raw wire output. Redact at capture time (Step 6) — never "capture now, redact later."
• Capture is observation, not modification. Do not use captured payloads to bypass server-side rate limits, replay another user's session, or activate a dark-launched capability without authorization.
• The output of this skill is an internal artifact. Public publication of wire findings goes through

  redact-for-public-disclosure

  (Phase 5 of the parent guide), not this skill.

When to Use

• A static finding (a flag, an endpoint reference, a telemetry-event name) needs runtime confirmation that it actually fires.
• A payload shape is needed for a client re-implementation, a tracing instrumentation, or a cross-version diff.
• Dark-vs-live disambiguation requires watching what the binary actually sends, not what the bundle suggests it might.
• A behavior changed silently between versions and you want a reproducible artifact to compare against future versions.

Do not use this skill for: version baselining (use

monitor-binary-version-baselines

), flag-state probing (use

probe-feature-flag-state

), or preparing redacted artifacts for public publication (use

redact-for-public-disclosure

).

Inputs

• Required: A CLI harness binary you can run locally against your own account.
• Required: A specific question to answer (e.g., "does endpoint X fire on event Y?", "what is the payload shape for telemetry event Z?"). Capture without a question produces a log that nobody reads.
• Optional: Static findings from prior phases (marker catalog, candidate flag list, suspected endpoints) that scope the capture targets.
• Optional: A private workspace path for capture artifacts. Default is

  ./captures/

  — must be in

  .gitignore

  .

Procedure

Step 1: Build the Observability Table First

Before configuring any capture, enumerate the questions you need to answer and map each to a capture channel. One row per target.

target	observable via	blocker
Outbound HTTP to endpoint X	verbose-fetch stderr	TUI noise pollutes terminal
Telemetry event Y on user action	hook-driven subprocess	requires harness hook surface
Token-refresh handshake	outbound HTTP proxy	cert trust required
Scheduled-task lifecycle event	long-running session capture	wallclock alignment
Local config mutation	on-disk state diff	none — cheapest channel

Common channels, cheapest first:

• On-disk state file mutation — when the harness writes its state to a known path,

  diff

  between snapshots is free.
• Transcript file — when the harness already writes a session transcript, parse it directly. No instrumentation.
• Verbose-fetch stderr — bundler-provided env var (e.g., bun's

  BUN_CONFIG_VERBOSE_FETCH=curl

  ) routes every fetch to stderr. Noisy but captures every fetch.
• Hook-driven subprocess — when the harness exposes lifecycle hooks (

  UserPromptSubmit

  ,

  Stop

  , etc.), spawn a short capture subprocess per event.
• Long-running session capture — one process across a session, wallclock-tagged. Use for sequences.
• Outbound HTTP proxy — clean separation, but requires CA cert trust and breaks when the harness pins certificates.

Pick the cheapest channel that captures the target. A 3-target capture that answers one specific question beats a 20-target capture that answers none.

Got: an observability table with one row per question, each annotated with channel and known blockers. Targets without a viable channel are flagged "out of scope this session."

If fail: if every target lands in the proxy column, the table is too ambitious. Trim to the one or two highest-value questions and revisit lower-cost channels for them.

Step 2: Prepare a Disposable Workspace

Wire capture pollutes terminals, leaves files in unexpected places, and may leak credentials into logs.

mkdir -p captures/$(date -u +%Y-%m-%dT%H-%M-%S)
cd captures/$(date -u +%Y-%m-%dT%H-%M-%S)
echo 'captures/' >> ../../.gitignore
git check-ignore captures/ || echo "WARNING: captures/ not git-ignored"

Confirm the capture session is not your primary working session — verbose-fetch and TUI rendering interfere with each other.

Got: a timestamped capture directory, git-ignored, separate from your working session.

If fail: if

git check-ignore

reports the directory as not ignored, fix

.gitignore

before running any capture command. Do not proceed with credentials at risk.

Step 3: Hook-Driven Capture for Per-Event Targets

When the target is a discrete event (a tool invocation, a prompt submission, a session stop), use the harness's hook surface. Spawn a short-lived capture subprocess per event; do not sit in-process.

The pattern (synthetic example):

# Hook script, registered with the harness's hook config.
# Invoked once per event; writes one JSONL line; exits.
#!/usr/bin/env bash
set -euo pipefail
TS=$(date -u +%Y-%m-%dT%H:%M:%S.%3NZ)
EVENT="${1:-unknown}"
PAYLOAD=$(jq -c --arg ts "$TS" --arg ev "$EVENT" \
  '{ts:$ts, source:"hook", target:$ev, payload:.}' < /dev/stdin)
echo "$PAYLOAD" >> "$CAPTURE_DIR/events.jsonl"

Why subprocess-per-event:

• No token state, no session coupling — each invocation is independent.
• Failure of one capture does not contaminate the next.
• Subprocess overhead is acceptable because events are rare (per-user-action, not per-byte).

Got: one JSONL line per fired event in

events.jsonl

, each well-formed JSON parseable with

jq

.

If fail: if

jq

reports parse errors, the payload contains unescaped control chars or binary data — pipe through

jq -R

(raw input) and base64-encode the payload field instead.

Step 4: Long-Running Session Capture for Sequential State

When the target is a sequence (multi-turn handshake, scheduled-task lifecycle, retry/backoff state machine), one capture process across the session, wallclock-tagged.

# Run the harness with verbose-fetch routed to a tee-d log.
BUN_CONFIG_VERBOSE_FETCH=curl harness-cli run-task 2> >(
  while IFS= read -r line; do
    printf '%s\t%s\n' "$(date -u +%Y-%m-%dT%H:%M:%S.%3NZ)" "$line"
  done >> "$CAPTURE_DIR/session.tsv"
)

The wallclock prefix makes ordering unambiguous when multiple captures run concurrently. TSV (tab-separated) is intentional — it survives shells that mangle JSON quoting on stderr.

Convert TSV to JSONL after the session ends (Step 5), not during.

Got: a TSV log with monotonically increasing timestamps, one stderr line per row.

If fail: if timestamps go backwards, the harness is buffering stderr — re-run with

stdbuf -oL -eL

or the bundler's equivalent line-buffer flag.

Step 5: Normalize to JSONL

JSONL is the artifact format: one JSON object per line, fields

timestamp

,

source

,

target

,

payload

. Diff-friendly,

jq

-filterable, and stable across editor reloads.

# Parse the TSV from Step 4 into JSONL.
awk -F'\t' '{
  printf "{\"timestamp\":\"%s\",\"source\":\"verbose-fetch\",\"target\":\"%s\",\"payload\":%s}\n",
    $1, "session", $2
}' < session.tsv | jq -c . > session.jsonl

Validate every line parses:

while IFS= read -r line; do
  echo "$line" | jq -e . > /dev/null || echo "BAD LINE: $line"
done < session.jsonl

Typical filter usage:

# Show only requests to a specific endpoint pattern.
jq -c 'select(.payload | tostring | test("/api/v1/example"))' session.jsonl

# Show timing between consecutive captures.
jq -r '.timestamp' session.jsonl | sort | uniq -c

Got: every line of

*.jsonl

parses with

jq -e .

; no

BAD LINE

warnings.

If fail: if some lines fail validation, the source TSV had embedded tabs in the payload — re-run Step 4 with a different delimiter or base64-encode the second field.

Step 6: Redact at Capture Time

Strip auth headers, session IDs, bearer tokens, and PII before writing to disk. The

events.jsonl

and

session.jsonl

files should not, on first write, contain a single secret.

# Stream the raw capture through a redactor before persisting.
redact() {
  sed -E \
    -e 's/(authorization:[[:space:]]*Bearer[[:space:]]+)[A-Za-z0-9._-]+/\1<REDACTED>/gi' \
    -e 's/(x-api-key:[[:space:]]*)[A-Za-z0-9._-]+/\1<REDACTED>/gi' \
    -e 's/(cookie:[[:space:]]*)[^;]+/\1<REDACTED>/gi' \
    -e 's/("password"[[:space:]]*:[[:space:]]*)"[^"]*"/\1"<REDACTED>"/g' \
    -e 's/("token"[[:space:]]*:[[:space:]]*)"[^"]*"/\1"<REDACTED>"/g'
}

cat raw-capture.txt | redact > session.tsv

After capture, verify nothing slipped through:

# Patterns that must not appear in any *.jsonl file.
grep -Ei 'bearer [A-Za-z0-9]{20,}|sk-[A-Za-z0-9]{20,}|ghp_[A-Za-z0-9]{20,}' captures/ \
  && { echo "LEAK DETECTED"; exit 1; } \
  || echo "redaction clean"

The

captured-then-redacted

artifact always leaks something. The only safe pattern is

redacted-as-captured

. If you discover an unredacted token in a finalized artifact, treat the entire capture as compromised — delete it, rotate the credential, and re-run.

Got: the

LEAK DETECTED

check exits 0 (no matches).

grep

for known credential prefixes returns nothing.

If fail: if the leak check finds a hit, do not edit the file in place. Delete the entire capture directory, extend the redactor regex to cover the leaked pattern category, and re-run from Step 3 or 4.

Step 7: Classify Response Categories Before Recording

HTTP status codes carry different semantic weight in different contexts. Classify before recording so downstream

jq

filters operate on intent, not raw codes.

Observed status	Channel context	Classification
200 / 201	Any	success
401 on token-refresh endpoint	Handshake	expected handshake step
401 on data endpoint	After auth	auth failure (real)
404 on lazy-loaded resource	First fetch	expected miss
404 on documented endpoint	After feature gate	gate-induced absence
429	Any	rate-limit (back off; do not retry tight)
5xx	Any	server failure (record, do not assume)

Add a

class

field at capture time:

jq -c '. + {class: (
  if (.payload.status == 401 and (.target | test("token|refresh"))) then "handshake"
  elif (.payload.status >= 200 and .payload.status < 300) then "success"
  elif (.payload.status == 401) then "auth-fail"
  elif (.payload.status == 429) then "rate-limit"
  elif (.payload.status >= 500) then "server-fail"
  else "other" end)}' session.jsonl > session.classified.jsonl

A 401 on a token-refresh channel is not a failure — it is the first half of a handshake. Misclassifying handshake steps as failures produces false-positive findings that waste reviewer attention.

Got: every line in

*.classified.jsonl

has a

class

field with a known value.

If fail: if classification produces many

other

entries, the table above is incomplete for this harness — extend it with one row per recurring

other

pattern before continuing analysis.

Step 8: Persist the Capture Manifest

A capture run is reproducible only if the inputs are recorded alongside the outputs. Write a manifest:

cat > capture-manifest.json <<EOF
{
  "captured_at": "$(date -u +%Y-%m-%dT%H:%M:%SZ)",
  "harness_version": "$(harness-cli --version 2>/dev/null || echo unknown)",
  "channel": "verbose-fetch",
  "question": "Does endpoint X fire on event Y?",
  "targets": ["endpoint-X", "event-Y"],
  "files": ["session.jsonl", "session.classified.jsonl"],
  "redaction_check": "passed"
}
EOF

The manifest is what makes the capture diff-able against future versions.

Got:

capture-manifest.json

exists, parses with

jq

, and lists every artifact file in the capture directory.

If fail: if the harness has no version flag, record the binary's

sha256sum

instead. An unidentified binary produces uncomparable captures.

Validation

• Observability table built before any capture command was run
• Capture directory is git-ignored and timestamped
• Every

  *.jsonl

  file parses with

  jq -e .

  line-by-line
• Redaction leak-check returns no matches for known credential prefixes
• Each captured event has a

  class

  field with a known value

• capture-manifest.json

  records the harness version (or sha256), channel, and question
• The capture directory contains only the targets enumerated in Step 1 (no incidental traffic from other apps)

Pitfalls

• Capture-first, question-later: a log nobody reads is wasted disk and wasted attention. Build the observability table first; capture only what answers a specific question.
• Reaching for

  mitmproxy

  first: outbound proxy is the most invasive channel. It requires cert trust, breaks on certificate pinning, and pollutes the harness's environment. Use it only when on-disk, transcript, verbose-fetch, and hook channels are all blocked.
• Capturing in your primary working session: verbose-fetch stderr bleeds into TUI rendering and can leak fragments of your other work into the capture. Always use a disposable shell.
• "We'll redact later": every captured-then-redacted artifact has leaked a credential at least once. Redact at capture time or do not capture.
• Treating 4xx as failure uniformly: a 401 on a token-refresh channel is a handshake step, not a failure. Classify response categories per channel context (Step 7) before drawing conclusions.
• Long-running capture for per-event targets: a session-long process to capture three discrete events couples token state across captures and makes one bad event poison the next. Use hook-driven subprocesses for events; reserve session capture for sequences.
• No manifest: a JSONL file without

  capture-manifest.json

  is not reproducible — you cannot diff it against next month's binary if you do not know which version produced it.
• Capturing other users' traffic: out of scope. Wire capture is for your own account on your own machine. If a capture incidentally records another user's request, delete the capture and tighten the channel.

Related Skills

• monitor-binary-version-baselines

  — Phase 1 of the parent methodology; produces the version baseline this skill's manifest references.

• probe-feature-flag-state

  — Phases 2-3; wire capture is one of its evidence prongs, and this skill teaches the capture half.

• instrument-distributed-tracing

  — shares the JSONL-over-wallclock philosophy; applied here to a single binary instead of a service mesh.

• redact-for-public-disclosure

  — Phase 5; this skill only covers capture-time redaction for internal use, not the publication-bar redaction needed before any capture leaves a private workspace.