observer

A background agent that studies records of your coding sessions and looks for repeated patterns. It can turn those patterns into reusable instincts for a specific project or for all projects.

In plain words
What is it for?
Use it to analyze recorded tool activity, detect recurring ways of working, create confidence-scored instincts, and run this analysis after enough observations or on a schedule.
Why use it?
It reduces the need to repeat the same instructions and working habits across sessions. Project-scoped instincts help keep lessons from one codebase separate from those belonging everywhere.

Agent

Install

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.

agentmods
npx agentmods add agents/nklofy/code-agent-skills/observer
Clone the repo
git clone --depth 1 https://github.com/nklofy/code-agent-skills
Per session 33 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,911 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 86% copy Near-identical to another mod 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 $0.00033 $0.01911
Opus 5 $0.00016 $0.00955
Sonnet 5 $0.00007 $0.00382
Haiku 4.5 $0.00003 $0.00191

Measured 2d ago against content hash d1fdf1a91ca3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 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.

Origin

This is a copy

86% identical to observer — 8 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.

affaan-m-ECC/continuous-learning-v2/agents/observer.md · 199 lines

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: ${XDG_DATA_HOME:-~/.local/share}/ecc-homunculus/projects/<project-hash>/observations.jsonl
  • Global fallback: ${XDG_DATA_HOME:-~/.local/share}/ecc-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"

Read the full file on GitHub · 199 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. 2d ago First seen · 199 lines · 33 tokens per session scan A d1fdf1a91ca3

Subscribe to this mod's changes

observer is an agent published in the GitHub repository nklofy/code-agent-skills (18 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 33 tokens to every session and 1,911 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to observer, differing in 8 lines, and is treated as a copy.