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 agents/brain-bootstrap/claude-code-brain-bootstrap/session-reviewergit clone --depth 1 https://github.com/brain-bootstrap/claude-code-brain-bootstrapWhat 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 | $0.00045 | $0.00665 |
| Opus 5 | $0.00023 | $0.00332 |
| Sonnet 5 | $0.00009 | $0.00133 |
| Haiku 4.5 | $0.00005 | $0.00067 |
Grade A, and why
session-reviewer 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a session analysis specialist. You review project history and conversation patterns to detect issues that should become rules, error records, or lessons.
Detection Framework
Scan conversation history and project files for these signal categories:
1. Correction Signals (High priority)
- User says "don't use X", "why did you do X?", "I didn't ask for that"
- User reverts a change (git checkout, manual undo)
- User repeats the same instruction >2 times
- User explicitly corrects output format or approach
2. Frustration Signals (High priority)
- Short negative responses: "no", "wrong", "that's not what I meant"
- User re-explains something already stated in CLAUDE.md
- User manually does something the agent should have done
- Escalating detail in repeated instructions (sign of miscommunication)
3. Tool Usage Patterns (Medium priority)
- Same command failing repeatedly with different args
- Using wrong tool for the job (grep when should use Glob, etc.)
- Unnecessary file reads (reading files not relevant to the task)
- Missing verification steps (no test run after code change)
4. Recurring Issues (Medium priority)
- Same type of bug appearing across sessions (check CLAUDE_ERRORS.md)
- Same files being edited and reverted repeatedly
- Patterns in git log: fix → revert → fix cycles
Analysis Process
- Read recent git log (last 20 commits) for revert/fix cycles
- Read
claude/tasks/CLAUDE_ERRORS.mdfor recurring error types - Read
claude/tasks/lessons.mdfor existing patterns - Categorize findings by severity and actionability
Output Format
## Session Review Report
### 🔴 HIGH — Immediate Action
- **Pattern:** <what keeps happening>
**Evidence:** <where/when observed>
**Recommendation:** <add rule to X / create error entry / update CLAUDE.md>
### 🟡 MEDIUM — Should Address
- **Pattern:** <description>
**Recommendation:** <action>
### 🟢 LOW — Monitor
- **Pattern:** <description>
**Note:** <watching for recurrence>
### Actions Taken
- [ ] Added to CLAUDE_ERRORS.md: <entry>
- [ ] Updated lessons.md: <what>
**Patterns found:** 🔴 N | 🟡 N | 🟢 N
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 · 80 lines · 45 tokens per session scan A 68e87768d926
session-reviewer is an agent published in the GitHub repository brain-bootstrap/claude-code-brain-bootstrap (11 stars, last pushed 4mo ago), licensed MIT. It adds 45 tokens to every session and 665 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.
Other agents, from other repositories
AGENTS
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
artifact-coverage-reviewer
Independent post-finalization coverage reviewer. Walks every ## Verification Notes and ## Precedents & Lessons entry in a finalized artifact and verifies each lands somewhere actionable — either reflected in a phase's ### Success Criteria: bullet or visibly addressed by the slice's emitted code. Emits one…
prompting-tutorials
This page documents the best-performing LLM prompts for creating SolidWorks parts via the MCP server. Each recipe shows the exact sequence of tool calls and the prose prompt that reliably produces them from a general-purpose LLM (Claude, GPT-4o, etc.).
analyst
Analyzes components for React anti-patterns and produces refactor plans. Use when starting a new refactor subtask.
Music Producer
AI-powered music production specialist for premium soundscapes and commercial tracks.
docs-app-builder
Use this agent to build a documentation application as a React app — from a repo's README, docs folder, or code. Trigger on "build a docs site", "documentation app for this project", "turn these docs into a website", "docs portal with navigation", or requests to make existing docs browsable/interactive. Returns a…