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 rampstackco/claude-skills-pm --skill after-action-reportgit clone --depth 1 https://github.com/rampstackco/claude-skills-pmWrote 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/rampstackco/claude-skills-pm/after-action-report)<a href="https://agentmods.dev/skills/rampstackco/claude-skills-pm/after-action-report"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills-pm/after-action-report/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/rampstackco/claude-skills-pm/after-action-report"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills-pm/after-action-report.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 | $0.00139 | $0.02231 |
| Opus 5.5 | $0.00056 | $0.00892 |
| Sonnet 5.5 | $0.00028 | $0.00446 |
| Haiku 4.5 | $0.00014 | $0.00223 |
Grade A, and why
after-action-report 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 19d 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.
This is a copy
91% identical to after-action-report — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
After-Action Report
Run a structured retrospective on a launch, incident, or completed project. Produce actionable lessons, not just a document.
This skill is for after-the-fact analysis. For active incident response, use incident-response. For planning launches, use launch-runbook.
When to use
- After any incident (any severity)
- After every major launch
- At the end of a project (sprint retro, quarterly retro, project closeout)
- When a recurring issue has happened enough times to demand investigation
- When a decision didn't work out and the team wants to learn
When NOT to use
- During an active incident (use
incident-response) - For pre-launch planning (use
launch-runbook) - For one-off bug fixes that don't merit broad analysis
Required inputs
- The event being analyzed (incident, launch, project)
- A timeline reconstructed from logs, chat, tickets
- Participant accounts of what they observed and did
- Outcomes and impact (what actually happened to users, the business)
The framework: blameless analysis
The most important principle: blameless. Without it, retrospectives produce hidden information and theatrical lessons rather than real ones.
What blameless means
- Focus on systems, not individuals
- Assume everyone made reasonable decisions given what they knew at the time
- The question is "why was this decision reasonable to make?" not "who screwed up?"
- Fixing the system means the next person in that situation succeeds where this person didn't
What blameless does not mean
- No accountability (action items still have owners)
- No hard truths (sometimes the system is broken in obvious ways)
- No standards (some patterns of failure are individual, not systemic)
- No discomfort (real reflection is uncomfortable)
The framework: 6 sections
A complete AAR covers six sections.
1. Summary
A 2 to 3 paragraph overview. Captures:
- What happened
- Impact (users, business, time)
- Root cause (in plain language)
- Top action items
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 19d ago Changed · +6 lines 97c20ae6885f
- 1mo ago First seen · 283 lines · 139 tokens per session scan A 89bcf92ced99
after-action-report is a skill published in the GitHub repository rampstackco/claude-skills-pm (4 stars, last pushed 6d ago), licensed MIT. It adds 139 tokens to every session and 2,231 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to after-action-report, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
after-action-report
Run a structured after-action review (postmortem, retrospective) on a launch, incident, or completed project to capture timeline, root cause analysis, contributing factors, and actionable lessons. Use this skill whenever the user wants to run a postmortem, retrospective, AAR, or after-action review on any past event.…
notion
Search, read, create, and update Notion pages via the Notion MCP.
alumni-re-hire-tracker
Alumni and re-hire register: former role, last working day, re-hire eligibility, current employer and re-engagement date, as CSV, SQL, JSON Schema or Notion on request. Use for alumni outreach.
parallel-feature-development
Coordinate parallel feature development with file ownership strategies, conflict avoidance rules, and integration patterns for multi-agent implementation. Use this skill when decomposing a large feature into independent work streams, when two or more agents need to implement different layers of the same system…
meeting-action-items
Turn meeting notes into cited decisions, owners, tickets.
create-stories
Breaks one epic into implementable stories with acceptance criteria. Use when the user wants stories for an epic or the next batch of work to build. Not for turning the whole design into epics.