Cognee is an AI memory platform that stores information in a self-hosted knowledge graph so agents can retain context across sessions. It ingests data, connects related information, and helps agents retrieve it for reasoning and actions. The catalogue includes skills and instructions that extend agent workflows around Cognee.
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 skills add topoteretes/cognee --skill skill-feedback-writergit clone --depth 1 https://github.com/topoteretes/cogneeWrote 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/topoteretes/cognee/skill-feedback-writer)<a href="https://agentmods.dev/skills/topoteretes/cognee/skill-feedback-writer"><img src="https://agentmods.dev/badge/skills/topoteretes/cognee/skill-feedback-writer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/topoteretes/cognee/skill-feedback-writer"><img src="https://agentmods.dev/badge/skills/topoteretes/cognee/skill-feedback-writer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00013 | $0.00179 |
| Opus 5 | $0.00006 | $0.00089 |
| Sonnet 5 | $0.00003 | $0.00036 |
| Haiku 4.5 | $0.00001 | $0.00018 |
Grade A, and why
skill-feedback-writer 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 9d 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.
What it actually says
skill-feedback-writer
You evaluate whether a skill's output was good enough for the task.
Focus on improving pr-comment-evaluator unless diff-risk-explainer failed to identify the main runtime risk. The pr-comment-evaluator is defective if it judges tone only or fails to compare the reviewer comment against the concrete runtime risk. In that case, target pr-comment-evaluator and set score to 0.30 or lower.
Return only JSON with these keys:
- diff_risk_summary
- comment_evaluation
- skill_to_improve
- score
- feedback
- missing_instruction
Use a score from 0.0 to 1.0. Give a low score when the evaluated skill misses a concrete, important requirement. The feedback must name the missing instruction clearly.
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.
- 9d ago First seen · 23 lines · 13 tokens per session scan A 26eabce5fee2
skill-feedback-writer is a skill published in the GitHub repository topoteretes/cognee (30,610 stars, last pushed today), licensed Apache-2.0. It adds 13 tokens to every session and 179 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 skills, from other repositories
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reflex-create
Use when the user notices a recurring pattern they want the system to learn ("I keep doing X", "every time Y happens", "make this automatic", "remember to always"), or when explicit phrases like "/reflex-create", "create reflex", "teach yourself" are used. Generates a new SKILL.md file from observed patterns.
surface-learnings
Use when the user asks "what have you learned", "what do you remember about me", "show me memory stats", "memory state", "/reflexes", or any variant. Surfaces what the limbic engine has accumulated as patterns, not as a memory dump.
context-recovery
Use at the start of every session, and especially after context compaction or a cold restart. Fires as the first action, before engaging with the user's opening message.
habituation-check
Use when tempted to repeat the same praise, the same status report, the same explanation, or the same reassurance. Fires as a suppression gate — not all repetition is useful.
session-consolidation
Use at the end of any meaningful session — when the user says goodbye, when major work completes, or when context is about to be lost. Fires once, captures the session's essence, prepares for tomorrow.