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/aaaaqwq/agi-super-team/observergit clone --depth 1 https://github.com/aAAaqwq/AGI-Super-TeamWrote 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/agents/aaaaqwq/agi-super-team/observer)<a href="https://agentmods.dev/agents/aaaaqwq/agi-super-team/observer"><img src="https://agentmods.dev/badge/agents/aaaaqwq/agi-super-team/observer.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 | $0.00033 | $0.01883 |
| Opus 5 | $0.00016 | $0.00941 |
| Sonnet 5 | $0.00007 | $0.00377 |
| Haiku 4.5 | $0.00003 | $0.00188 |
Grade A, and why
observer 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 today.
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.
This is a copy
100% identical to observer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Observer Agent
A background agent that analyzes observations from Claude Code sessions to detect patterns and create instincts.
When to Run
- After enough observations accumulate (configurable, default 20)
- On a scheduled interval (configurable, default 5 minutes)
- When triggered on demand via SIGUSR1 to the observer process
Input
Reads observations from the project-scoped observations file:
- Project:
~/.claude/homunculus/projects/<project-hash>/observations.jsonl - Global fallback:
~/.claude/homunculus/observations.jsonl
{"timestamp":"2025-01-22T10:30:00Z","event":"tool_start","session":"abc123","tool":"Edit","input":"...","project_id":"a1b2c3d4e5f6","project_name":"my-react-app"}
{"timestamp":"2025-01-22T10:30:01Z","event":"tool_complete","session":"abc123","tool":"Edit","output":"...","project_id":"a1b2c3d4e5f6","project_name":"my-react-app"}
{"timestamp":"2025-01-22T10:30:05Z","event":"tool_start","session":"abc123","tool":"Bash","input":"npm test","project_id":"a1b2c3d4e5f6","project_name":"my-react-app"}
{"timestamp":"2025-01-22T10:30:10Z","event":"tool_complete","session":"abc123","tool":"Bash","output":"All tests pass","project_id":"a1b2c3d4e5f6","project_name":"my-react-app"}
Pattern Detection
Look for these patterns in observations:
1. User Corrections
When a user's follow-up message corrects Claude's previous action:
- "No, use X instead of Y"
- "Actually, I meant..."
- Immediate undo/redo patterns
→ Create instinct: "When doing X, prefer Y"
2. Error Resolutions
When an error is followed by a fix:
- Tool output contains error
- Next few tool calls fix it
- Same error type resolved similarly multiple times
→ Create instinct: "When encountering error X, try Y"
3. Repeated Workflows
When the same sequence of tools is used multiple times:
- Same tool sequence with similar inputs
- File patterns that change together
- Time-clustered operations
→ Create workflow instinct: "When doing X, follow steps Y, Z, W"
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.
- today First seen · 199 lines · 33 tokens per session scan A 654f2f0fc9d9
observer is an agent published in the GitHub repository aAAaqwq/AGI-Super-Team (91 stars, last pushed yesterday), licensed MIT. It adds 33 tokens to every session and 1,883 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to observer, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
knowledge-extractor
Extracts reusable patterns, pitfalls, and decisions from completed work and writes them to the wiki staging area. Run after finishing a body of work to capture what was learned. Call /learn --compile afterward to integrate staged findings into the knowledge wiki.
memory-keeper
Updates .claude/memory.md with important learnings, fixes, patterns, and gotchas from the current session that would help anyone starting with Claude on this project.
agent-session
Trinity has two conversation surfaces, and the difference is memory.
universal
Paste this into your agent/LLM system instruction block.
memory-proposal-collector
Reference documentation (NOT a dispatchable agent) for the coordinator-direct AUQ rendering flow at session-end Phase 3.6.3. The coordinator collects proposals from .orchestrator/metrics/proposals.jsonl via collectProposals() and renders the multiSelect AUQ in batches of 4. Approved proposals flow to learnings.jsonl…
pi
Runtime.