mcpbeat Sign in

Aar Agent Skill

After-Action Review—structured debrief asking what was expected, what happened, why the difference, and what next. Use after projects, launches, presentations, or any significant event.

4k tokens
context cost
the whole folder, loaded on every use
4
files
instructions only
1
copies elsewhere
how many repositories repackaged it
106
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/neurofoo/agent-skills --skill aar

What comes with it

13 337 bytes besides the instruction
commands/aar.md
commands/review.md
references/examples.md

The instruction itself

8 sections, as written by the author

After-Action Review

Conduct a structured debrief to extract learning from any significant event or experience.

Instructions

Work through the four core questions honestly and specifically. Focus on events and systems, not blaming individuals.

Output Format

Event: What are we reviewing?

Date: When did it happen?

Participants: Who was involved?


1. What Was Expected?

*Before the event, what did we think would happen?*

Goals/Objectives

  • [What were we trying to achieve?]

Plan

  • [What was the plan to achieve it?]

Success Criteria

  • [How would we know if we succeeded?]

Assumptions

  • [What did we assume would be true?]

2. What Actually Happened?

*Facts only—what occurred, not why*

Timeline

| Time | Event |

|------|-------|

| [When] | [What happened] |

Outcomes

  • [What results did we get?]

Compared to Expected

| Expected | Actual | Gap |

|----------|--------|-----|

| [expectation] | [reality] | [+/-] |


3. Why the Difference?

*Analysis of the gap between expected and actual*

What Went Well (sustain these)

| Success | Contributing Factors |

|---------|---------------------|

| [what worked] | [why it worked] |

What Didn't Go Well (improve these)

| Problem | Root Cause |

|---------|-----------|

| [what failed] | [why it failed] |

Surprises

  • [Things we didn't anticipate]

4. What Do We Do Next?

*Specific actions to sustain or improve*

Sustain (keep doing these)

| Action | Owner | How to Protect It |

|--------|-------|-------------------|

| [what to continue] | [who] | [mechanism] |

Improve (change these)

| Action | Owner | By When |

|--------|-------|---------|

| [what to change] | [who] | [deadline] |


Key Takeaways

Top 3 lessons from this review:

  • [Lesson]
  • [Lesson]
  • [Lesson]

Follow-up

When will we check if improvements are working?

Guidelines

  • Do this soon—memory fades fast
  • Be specific: "Communication failed" → "We didn't update Slack until hour 3"
  • Balance: Include what went well, not just problems
  • Assign owners: Insights without ownership become forgotten
  • Make it safe: Blame shuts down honesty

$ARGUMENTS

Other skills for the same job

different authors, same section of the catalogue
Protocolsio Integration
by christophacham
×4

Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.

16k tokens
Tailored Resume Generator
by frostant
×4

Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances

3k tokens
Excalidraw Diagram Generator
by github
vendor ×3

Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.

36k tokens scripts
Expo Dev Client
by openai
vendor ×3

Build and distribute Expo development clients locally or via TestFlight

961 tokens
Executing Plans
by ZhanlinCui
×3

Use when you have a written implementation plan to execute in a separate session with review checkpoints

542 tokens
Anndata
by christophacham
×3

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

16k tokens
Benchling Integration
by christophacham
×3

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

14k tokens
Biopython
by christophacham
×3

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.

24k tokens

How to use it

Copy the folder

Take neurofoo/aar from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.