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.
git clone --depth 1 https://github.com/serein431/DoneGraphnpx agentmods add skills/serein431/donegraph/donegraph-recapWrote 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/serein431/donegraph/donegraph-recap)<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>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 | $0.00034 | $0.00626 |
| Opus 5 | $0.00017 | $0.00313 |
| Sonnet 5 | $0.00007 | $0.00125 |
| Haiku 4.5 | $0.00003 | $0.00063 |
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.
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:
itemsshould be 5-10 meaningful events, NOT one per commit — group related commits into logical stepsstoryshould be warm and human, not mechanical — tell what happened and why it mattersrisksshould flag real concerns (missing tests, breaking changes, security implications), not generic warningsinsightsshould 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:
- Run project checks (test, typecheck, build) automatically
- Use your AI analysis for the narrative and events
- Generate a visual dashboard with your story, insights, and risks
- Open it in the browser
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.
- 8d ago First seen · 68 lines · 34 tokens per session scan A 0b76a40ae1d2
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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