donegraph-recap

donegraph-recap is a skill for Claude Code from serein431/DoneGraph. It costs 34 tokens per session (626 once invoked), scanned A, original, MIT.

A command that summarizes a recent coding session by examining Git history, running checks, and creating a visual dashboard with a narrative, findings, risks, and next steps.

In plain words
What is it for?
Use it after a work session to review changes, verification results, risks, insights, and recommended follow-up work.
Why use it?
It gathers scattered evidence from the session into a readable account of what happened and what remains uncertain.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is ../../scripts/donegraph recap --analysis .donegraph/analysis.json --lang en $ARGUMENTS.

Part of the donegraph plugin — 9 skills shipped together

Good fit Use it after a work session to review changes, verification results, risks, insights, and recommended follow-up work.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/serein431/DoneGraph
agentmods
npx agentmods add skills/serein431/donegraph/donegraph-recap

Made for: Claude Code.

Or install donegraph, the plugin that ships this one along with the rest of its 9 skills.

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 donegraph-recap

README.md
[![agentmods](https://agentmods.dev/badge/skills/serein431/donegraph/donegraph-recap.svg)](https://agentmods.dev/skills/serein431/donegraph/donegraph-recap)
Your own site
<a href="https://agentmods.dev/skills/serein431/donegraph/donegraph-recap"><img src="https://agentmods.dev/badge/skills/serein431/donegraph/donegraph-recap.svg" alt="Measured on agentmods" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 626 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 $0.00034 $0.00626
Opus 5 $0.00017 $0.00313
Sonnet 5 $0.00007 $0.00125
Haiku 4.5 $0.00003 $0.00063

Measured 8d ago against content hash 0b76a40ae1d2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

donegraph-recap 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 8d 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.

plugins/donegraph/skills/donegraph-recap/SKILL.md · 68 lines

How it starts

The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/donegraph-recap

Generate an AI-powered visual recap of the current working session.

Step 1: Gather context

Run these commands and read the output:

git log --oneline -20
git diff --stat HEAD~5 2>/dev/null || git diff --stat

Step 2: Analyze and write analysis JSON

Based on the git output, write your analysis to .donegraph/analysis.json in this exact format:

{
  "version": "1",
  "summary": "One-sentence summary of what this session accomplished",
  "story": "A 2-3 sentence narrative telling the story of this work session — what problem was tackled, how it was approached, and what the outcome was. Write like a thoughtful colleague summarizing the day, not like a changelog.",
  "items": [
    {
      "title": "Short title of what was done",
      "detail": "Why this matters or what it achieved",
      "type": "goal|decision|action|artifact|verification|completion",
      "status": "pass|fail|unknown"
    }
  ],
  "risks": ["Any risks or concerns spotted in the changes"],
  "insights": ["Non-obvious observations about the work pattern or code quality"],
  "next_steps": ["What should happen next based on this session"]
}

Guidelines for writing the analysis:

  • items should be 5-10 meaningful events, NOT one per commit — group related commits into logical steps
  • story should be warm and human, not mechanical — tell what happened and why it matters
  • risks should flag real concerns (missing tests, breaking changes, security implications), not generic warnings
  • insights should be genuinely useful observations (patterns, architecture decisions, quality trends)
  • Use type: "goal" for the first item, type: "completion" for the last, and appropriate types in between

Step 3: Run recap with analysis

../../scripts/donegraph recap --analysis .donegraph/analysis.json --lang en $ARGUMENTS

This will:

  1. Run project checks (test, typecheck, build) automatically
  2. Use your AI analysis for the narrative and events
  3. Generate a visual dashboard with your story, insights, and risks
  4. Open it in the browser

Read the full file on GitHub · 68 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. 8d ago First seen · 68 lines · 34 tokens per session scan A 0b76a40ae1d2

Subscribe to this mod's changes

donegraph-recap is a skill published in the GitHub repository serein431/DoneGraph (23 stars, last pushed 2mo ago), licensed MIT. It adds 34 tokens to every session and 626 once invoked, about $0.0002 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 2026-08-30.

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