원클릭으로 Manus에서 모든 스킬 실행

run-trace

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업데이트2026년 7월 5일 07:23

Append structured execution traces across operational, cognitive, and contextual surfaces with minimal overhead. Load when inspecting agent runs, logging tool calls and observations, enabling post-run debugging, or pairing with structured-planning step IDs. Also triggers on "trace this run", "log execution", "agent observability", "run log", or when fault-localize needs evidence. Default-on during multi-step plans. Traces live at .agent-loom/traces/ — git-ignored by default.

설치

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

Manus에서 실행

출처

dvy1987

dvy1987/agent-loom

GitHub 저장소 열기 Creator 저장소 보기

다운로드

Manus에서 실행

Run Trace

You append low-overhead, structured records per meaningful step — tool call, observation, reflection, error. Three surfaces: operational, cognitive, contextual. Never block execution to log.

Hard Rules

Append to .agent-loom/traces/<run-id>.jsonl — one JSON object per line per references/TRACE-SCHEMA.md. Reuse step_id from active structured-planning plan when present. Never persist secrets — refs only in input_ref / output_ref. Logging is append-only — never rewrite prior lines. Ensure .agent-loom/traces/ is gitignored in consumer projects.

Workflow

Step 1 — Allocate run_id

Format: YYYY-MM-DDTHH:MM:SSZ-<slug> at run start. Create empty jsonl file.

Step 2 — Append per step

After each meaningful event, append one record with correct surface:

Event	Surface
Tool/command executed	operational
Plan/route/reflection	cognitive
cwd, branch, versions	contextual

Step 3 — On error

Set error field on the operational record. Continue tracing if run continues.

Step 4 — Query when needed

python3 .agents/skills/run-trace/scripts/trace_query.py <path> timeline
python3 .agents/skills/run-trace/scripts/trace_query.py <path> errors

Step 5 — Hand off

On failed run, pass trace path to fault-localize.

Gotchas

Pretty-printed JSON breaks JSONL — single-line objects only.
Logging raw env vars may leak secrets — whitelist keys only.
High-frequency polling loops — batch or sample; don't log every poll.

Output Format

## Run trace — [run_id]

Trace file: `.agent-loom/traces/[run_id].jsonl`
Records: N | Errors: N

Latest:
- [ts] [surface] [step_id] [action]

Query: trace_query.py [path] timeline

Examples

Teaser: 5-step plan run → 12 operational + 3 cognitive records → S3 error captured with exit code.

Full pairs: references/examples.md

Common Rationalizations

Excuse	Reality
"Tracing is too heavy"	One JSON line per step is cheap.
"I'll remember what happened"	You won't — especially after revert.
"Chat history is enough"	Not structured; can't query errors programmatically.
"Secrets in output are fine locally"	Traces get committed, shared, uploaded — refs only.
"Skip cognitive surface"	Route decisions are the hardest to debug.

Verification

Trace file exists and is valid JSONL
step_ids align with plan when planning active
No secrets in trace payloads
traces/ gitignored

Red Flags

Trace file with invalid JSON lines
Missing error field on failed tool steps
Secrets written to jsonl

Prune Log

Last pruned: 2026-07-05

Initial release from high-leverage skill spec (Skill 4 family)

Impact Report

Trace: [run_id] | Records: N | Errors: N | Path: .agent-loom/traces/...

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Review code changes for correctness, completeness, bugs, edge cases, and quality. Load when the user explicitly asks to review code, check a PR, review a diff, audit recent changes, or verify an implementation matches requirements. Also triggers on "review this code", "check this PR", "review my changes", "code review", "did this implement correctly", "audit this diff", or any explicit request for a formal code review. Do NOT load for "review changes for context" or "review what happened" — those are requests to read code, not to perform a formal review.

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Fix broken or failing functionality through structured reproduction, root-cause analysis, minimal fix, and verification. Load when the user asks to fix a bug, debug an error, resolve an issue, or work on a Linear ticket. Also triggers on "this is broken", "fix this bug", "why is this failing", "debug this", "resolve this error", "what went wrong", or any request to diagnose and fix a problem.

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Structure git work with atomic commits, conventional messages, short-lived branches, and pre-commit hygiene. Load when committing, branching, resolving merge conflicts, organizing parallel work, or reviewing git history. Also triggers on "git workflow", "commit message", "conventional commits", "atomic commit", "branch strategy", "git worktree", "how should I commit this". Does not replace project-specific hook policies — complements them.

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Deliver multi-file changes in thin vertical slices — implement, test, verify, commit, repeat. Load when implementing a feature from a plan, building across more than one file, refactoring, or when tempted to land a large change in one pass. Also triggers on "incremental implementation", "vertical slice", "thin slice", "one slice at a time", "don't do it all at once". Routes single-file fixes to direct execution. Pairs with test-driven-development and git-workflow-and-versioning.

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Apply the Red-Green-Refactor cycle to software development. Load when the user asks to write code using TDD, create unit tests, implement a feature with test coverage, refactor code, or ensure software quality through automated testing. Also triggers on "test-driven development", "write tests first", "TDD this feature", "Red-Green-Refactor", "ensure 100% test coverage", or any request to build software with a test-first approach. Supports unit, integration, and end-to-end testing strategies.

2026-07-093

name	run-trace
description	Append structured execution traces across operational, cognitive, and contextual surfaces with minimal overhead. Load when inspecting agent runs, logging tool calls and observations, enabling post-run debugging, or pairing with structured-planning step IDs. Also triggers on "trace this run", "log execution", "agent observability", "run log", or when fault-localize needs evidence. Default-on during multi-step plans. Traces live at .agent-loom/traces/ — git-ignored by default.
license	MIT
metadata	{"author":"dvy1987","version":"1.0","category":"project-specific","sources":"AgentTrace arXiv 2602.10133, Watson arXiv 2411.03455","resources":{"references":["TRACE-SCHEMA.md","examples.md"],"scripts":["trace_query.py"]}}

Run Trace

You append low-overhead, structured records per meaningful step — tool call, observation, reflection, error. Three surfaces: operational, cognitive, contextual. Never block execution to log.

Hard Rules

Workflow

Step 1 — Allocate run_id

Format: YYYY-MM-DDTHH:MM:SSZ-<slug> at run start. Create empty jsonl file.

Step 2 — Append per step

After each meaningful event, append one record with correct surface:

Event	Surface
Tool/command executed	operational
Plan/route/reflection	cognitive
cwd, branch, versions	contextual

Step 3 — On error

Set error field on the operational record. Continue tracing if run continues.

Step 4 — Query when needed

python3 .agents/skills/run-trace/scripts/trace_query.py <path> timeline
python3 .agents/skills/run-trace/scripts/trace_query.py <path> errors

Step 5 — Hand off

On failed run, pass trace path to fault-localize.

Gotchas

Pretty-printed JSON breaks JSONL — single-line objects only.
Logging raw env vars may leak secrets — whitelist keys only.
High-frequency polling loops — batch or sample; don't log every poll.

Output Format

## Run trace — [run_id]

Trace file: `.agent-loom/traces/[run_id].jsonl`
Records: N | Errors: N

Latest:
- [ts] [surface] [step_id] [action]

Query: trace_query.py [path] timeline

Examples

Teaser: 5-step plan run → 12 operational + 3 cognitive records → S3 error captured with exit code.

Full pairs: references/examples.md

Common Rationalizations

Excuse	Reality
"Tracing is too heavy"	One JSON line per step is cheap.
"I'll remember what happened"	You won't — especially after revert.
"Chat history is enough"	Not structured; can't query errors programmatically.
"Secrets in output are fine locally"	Traces get committed, shared, uploaded — refs only.
"Skip cognitive surface"	Route decisions are the hardest to debug.

Verification

Trace file exists and is valid JSONL
step_ids align with plan when planning active
No secrets in trace payloads
traces/ gitignored

Red Flags

Trace file with invalid JSON lines
Missing error field on failed tool steps
Secrets written to jsonl

Prune Log

Last pruned: 2026-07-05

Initial release from high-leverage skill spec (Skill 4 family)

Impact Report

Trace: [run_id] | Records: N | Errors: N | Path: .agent-loom/traces/...