long-task-retrospective

long-task-retrospective is a skill for Claude Code, Codex from megamen32/agent-resume. It costs 70 tokens per session (672 once invoked), scanned A, original, MIT.

A review tool for finished or failed Codex tasks that took unusually long, repeated work, or used many tools or tokens. It examines available records to explain what happened and what could improve.

In plain words
What is it for?
Use it after a task ends to build a short timeline, find the largest time sinks, classify delays, and record process improvements.
Why use it?
It helps separate unavoidable waiting from preventable delays instead of guessing why a task was slow. It can preserve up to three durable improvements, without changing product code.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; reads ~/.codex paths; mentions AGENTS.md.

Good fit Use it after a task ends to build a short timeline, find the largest time sinks, classify delays, and record process improvements.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/megamen32/agent-resume/long-task-retrospective
Install

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.

Any agent
npx skills add megamen32/agent-resume --skill long-task-retrospective
Clone the repo
git clone --depth 1 https://github.com/megamen32/agent-resume

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for long-task-retrospective

README.md
[![agentmods](https://agentmods.dev/badge/skills/megamen32/agent-resume/long-task-retrospective/github.svg)](https://agentmods.dev/skills/megamen32/agent-resume/long-task-retrospective)
Your own site
<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.

agentmods 80×15 button for long-task-retrospective

Your own site · 80×15
<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>
Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 672 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00070 $0.00672
Opus 5.5 $0.00028 $0.00269
Sonnet 5.5 $0.00014 $0.00134
Haiku 4.5 $0.00007 $0.00067

Measured 2mo ago against content hash 2d154d96841a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 2mo 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.

skills/long-task-retrospective/SKILL.md · 87 lines

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:

  1. Current session transcript and timestamps.
  2. Tool, MCP, job, command, and sub-agent logs.
  3. Git diff/status, tests, releases, and produced artifacts.
  4. OpenTelemetry spans when available.
  5. Existing AGENTS.md, skills, and project documentation.

Do not invent durations or causes. Mark conclusions uncertain when evidence is missing.

Analysis

  1. Reconstruct a compact phase timeline with elapsed time, result, and evidence.
  2. Identify the three largest time sinks.
  3. Separate unavoidable waiting from preventable delay.
  4. 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.
  5. For each major delay record evidence, root cause, earliest detection point, faster alternative, and estimated saving.
  6. 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.

Read the full file on GitHub · 87 lines

Changes

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.

  1. 2mo ago First seen · 87 lines · 70 tokens per session scan A 2d154d96841a

Subscribe to this mod's changes

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 5.5. 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.

Related

long-task-retrospective compared with skills from other repositories

long-task-retrospective next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
long-task-retrospectivemegamen32/agent-resumeSkill028d agoMITA70Claude Code, Codex
imagegenopenai/codexSkill134kyesterdayApache-2.0A113Codex
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79k2d agoMITA200Claude Code, Codex
playwright-climicrosoft/playwrightSkill100ktodayApache-2.0A19Claude Code
browser-automationopenclaw/openclawSkill394ktodayMITA36Claude Code
systematic-debuggingobra/superpowersSkill315k6d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143kyesterdayMITA95Claude Code