Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add megamen32/agent-resume --skill long-task-retrospectivegit clone --depth 1 https://github.com/megamen32/agent-resumeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/megamen32/agent-resume/long-task-retrospective)<a href="https://agentmods.dev/skills/megamen32/agent-resume/long-task-retrospective"><img src="https://agentmods.dev/badge/skills/megamen32/agent-resume/long-task-retrospective/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/megamen32/agent-resume/long-task-retrospective"><img src="https://agentmods.dev/badge/skills/megamen32/agent-resume/long-task-retrospective.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.00672 |
| Opus 5 | $0.00035 | $0.00336 |
| Sonnet 5 | $0.00014 | $0.00134 |
| Haiku 4.5 | $0.00007 | $0.00067 |
Grade A, and why
long-task-retrospective scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Long-task retrospective
Run only after the target task has completed or failed. If work is still running, use agent-resume to wait durably and resume the same session; do not perform a retrospective yet.
Budget
- One retrospective pass.
- At most 15 minutes or 25 tool calls.
- No product-code changes.
- No broad repository scan.
- Stop after the report and minimal durable updates are complete.
Evidence
Prefer, in order:
- Current session transcript and timestamps.
- Tool, MCP, job, command, and sub-agent logs.
- Git diff/status, tests, releases, and produced artifacts.
- OpenTelemetry spans when available.
- Existing
AGENTS.md, skills, and project documentation.
Do not invent durations or causes. Mark conclusions uncertain when evidence is missing.
Analysis
- Reconstruct a compact phase timeline with elapsed time, result, and evidence.
- Identify the three largest time sinks.
- Separate unavoidable waiting from preventable delay.
- Classify major delays, including:
- missing prerequisite or weak acceptance gate;
- wrong initial hypothesis;
- repeated materially identical attempts;
- unchanged polling or unnecessary coordination;
- broad exploration, rereading, or context loss;
- unnecessary or insufficient delegation;
- over-verification or scope creep;
- model, API, network, build, test, MCP, or infrastructure latency.
- For each major delay record evidence, root cause, earliest detection point, faster alternative, and estimated saving.
- Describe an efficient counterfactual execution path.
Persistence policy
Inspect existing instructions first. Avoid duplicate or contradictory rules.
Route findings as follows:
- Stable cross-project requirement:
~/.codex/AGENTS.md. - Stable project invariant: nearest project
AGENTS.md. - Reusable workflow: project or global skill.
- Incident-specific evidence:
docs/agent-retrospectives/YYYY-MM-DD-<slug>.md. - Temporary detail: final report only.
Add no more than three durable rules. Each rule must be evidence-backed, specific, measurable, and likely to prevent recurrence. Prefer stop conditions, retry limits, progress definitions, preflight gates, and escalation thresholds over vague advice.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 87 lines · 70 tokens per session scan A 2d154d96841a
long-task-retrospective is a skill published in the GitHub repository megamen32/agent-resume (0 stars, last pushed 28d ago), licensed MIT. It adds 70 tokens to every session and 672 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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