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 skills/onixhdz/cartograph/feedback-loopnpx skills add onixhdz/cartograph --skill feedback-loopgit clone --depth 1 https://github.com/onixhdz/cartographWrote 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/onixhdz/cartograph/feedback-loop)<a href="https://agentmods.dev/skills/onixhdz/cartograph/feedback-loop"><img src="https://agentmods.dev/badge/skills/onixhdz/cartograph/feedback-loop.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 | $0.00015 | $0.02074 |
| Opus 5 | $0.00008 | $0.01037 |
| Sonnet 5 | $0.00003 | $0.00415 |
| Haiku 4.5 | $0.00002 | $0.00207 |
Grade A, and why
feedback-loop scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feedback Loop — Iterative Algorithm Improvement
Drive measurable improvements to cartograph's analysis, ranking, and query algorithms by executing an evaluate → diagnose → fix → re-index → re-evaluate cycle until every acceptance criterion in the feedback plan passes.
Prerequisites
- A feedback plan file exists in
plans/(e.g.,plans/cartograph-feedback-nomad-eval.md). - The target repository is already indexed or can be indexed with
cartograph analyze. - The
cartographbinary can be built withtask build:devfrom the workspace root. cartographis already on$PATHvia dev symlink.
Workflow
Repeat the cycle below until all acceptance criteria in the plan pass or you are confident no further code changes can improve results.
Phase 0 — Read the Feedback Plan
- Read the feedback plan file end-to-end. Identify:
- Acceptance criteria — the numbered pass/fail conditions at the top.
- Reproduction commands — the exact
cartographinvocations to run. - Remaining issues — the narrative descriptions of what is still broken.
- Scores — the per-capability scores and overall target.
- Build a todo list from the acceptance criteria so progress is trackable.
Phase 1 — Build & Start Service
- Kill the running binary and stop the background service before building to ensure the old binary is not held by a running process and the new binary is picked up cleanly:
This is a no-op if no process or service is running.pkill -f cartograph 2>/dev/null || true cartograph serve stop 2>/dev/null || true - Run
cd /workspaces/cartograph && task build:devto compile the updated binary. - If the build fails, fix compilation errors before proceeding.
- Start the background service so queries can be dispatched in parallel:
Wait briefly for the service to be ready before proceeding to evaluation.cartograph serve start
Phase 2 — Evaluate
- Run every reproduction command from the plan exactly as written.
- With the service running, dispatch independent queries in parallel to speed up evaluation. Group queries that don't depend on each other and launch them concurrently.
- Capture output for each command.
- For cypher queries, pipe through
head -40to keep output manageable.
- For each acceptance criterion, record pass or fail with a one-line evidence note.
- If all criteria pass, stop — report success and the final scores.
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.
- 3d ago First seen · 142 lines · 15 tokens per session scan A e09dd356374c
feedback-loop is a skill published in the GitHub repository onixhdz/cartograph (11 stars, last pushed 17d ago), licensed MIT. It adds 15 tokens to every session and 2,074 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.
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