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 agentmods add commands/benkapner/claude-code-basecamp/recapgit clone --depth 1 https://github.com/Benkapner/claude-code-basecampWhat 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 | $0.00026 | $0.00628 |
| Opus 5 | $0.00013 | $0.00314 |
| Sonnet 5 | $0.00005 | $0.00126 |
| Haiku 4.5 | $0.00003 | $0.00063 |
Grade A, and why
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 2d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Recap Command
Summarize the current work session into a structured, shareable update.
Instructions
Step 1: Gather What Happened
# Recent commits (this session's work)
git log --oneline --since="8 hours ago" 2>/dev/null || git log --oneline -15
# What files changed
git diff --stat HEAD~10..HEAD 2>/dev/null || git diff --stat
# Current status
git status --short
Also review the conversation history for:
- What the user asked for
- Key decisions made (and why)
- Problems encountered and how they were solved
- Skills, agents, or commands that were used
Step 2: Generate the Recap
Format the output like this:
SESSION RECAP
=============
Date: [today's date]
Repo: [repository name]
WHAT WAS DONE:
1. [Change #1 — one sentence describing what and why]
2. [Change #2 — one sentence]
3. [Change #3 — one sentence]
...
KEY DECISIONS:
- [Decision and reasoning — e.g., "Kept closed issues as lightweight entries
instead of removing them, to give the AI context about completed work"]
- [Decision and reasoning]
PROBLEMS SOLVED:
- [Problem → Solution — e.g., "Merge conflict on executive_report.html
→ skipped local commit, kept remote version"]
FILES CHANGED:
[X] files modified, [Y] files created, [Z] files deleted
TESTS:
[All N tests passing / X failures]
READY TO SHARE (copy-paste for standup/Slack/email):
──────────────────────────────────────────────────────
[2-3 sentence summary suitable for a non-technical audience.
Focus on WHAT was accomplished and WHY it matters,
not the technical details of HOW.]
──────────────────────────────────────────────────────
Step 3: Offer Follow-ups
After the recap, ask:
- "Want me to adjust the tone (more technical / more executive)?"
- "Want me to expand any section?"
- "Want me to draft a message for a specific person?"
Important
- The "READY TO SHARE" section should be copy-pasteable as-is — no markdown, no jargon
- Focus on outcomes ("split the pipeline for easier debugging") not mechanics ("edited 14 files")
- If multiple repos were touched, organize by repo
- Include commit hashes for traceability
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.
- 2d ago First seen · 89 lines · 26 tokens per session scan A c1c995680ca3
recap is a command published in the GitHub repository Benkapner/claude-code-basecamp (16 stars, last pushed 13d ago), licensed MIT. It adds 26 tokens to every session and 628 once invoked, about $0.0001 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.
Other commands, from other repositories
spec-forge
Use when generating software specifications — full chain (Idea→Decompose→Tech Design + Feature Specs) or individual documents.
propagate
Use after editing an upstream doc (PRD/SRS/tech-design/feature-spec) to propagate changes downstream and keep the entire doc chain consistent.
analyze
Use when analyzing a document collection to map themes, find conflicts, gaps, and redundancies — generates landscape analysis report.
review
Use when reviewing spec-forge generated documents for quality, completeness, and consistency — auto-fixes issues if found.
audit
Use when auditing existing project docs for quality, completeness, and code alignment — generates findings report with fix recommendations.
tech-design
Use when writing a tech design, architecture doc, RFC, or design document — follows Google Design Doc format.