Borrowing it
Nothing to install: this file belongs to egregore-labs/egregore. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/egregore-labs/egregore/main/.claude/skills/reflect/SKILL.mdgit clone --depth 1 https://github.com/egregore-labs/egregoreWrote 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/egregore-labs/egregore/reflect)<a href="https://agentmods.dev/skills/egregore-labs/egregore/reflect"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/reflect/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/egregore-labs/egregore/reflect"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/reflect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 501 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
- medium Excessive Agency · line 213 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00057 | $0.00753 |
| Opus 5.5 | $0.00023 | $0.00301 |
| Sonnet 5.5 | $0.00011 | $0.00151 |
| Haiku 4.5 | $0.00006 | $0.00075 |
Grade A, and why
reflect 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 24d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reflect
Turn a settled insight into one to three typed, share-ready knowledge artifacts.
When to invoke
Use when the user says 'we decided', 'I realized', or 'that's a pattern' — captures a share-ready decision, finding, or pattern in canonical organizational memory. Use /note for private or half-baked thoughts and /archive for reusable AI-steering techniques.
Modes
- No arguments: use a short Socratic flow grounded in this session.
about <topic>: focus the flow on that topic.[decision|finding|pattern]: <content>: honor the explicit type.- Other arguments: quick capture; infer the type, defaulting to
finding.
Context
Reuse attached EGREGORE_ORG_CONTEXT_V1 evidence. When it is sufficient, do
not search or reopen sources. If a named gap remains, make one
bash bin/search.sh query "<concept>" -n 6 call and open only the missing
canonical source through bash bin/search.sh open. Never query implementation
infrastructure or storage directly.
Flow
- Extract the title, exact insight, context, rationale, two to four topics, workstream, explicit relationships, and superseded artifact IDs when known.
- Classify each distinct insight as
decision,finding, orpattern. Create at most three. Do not infer supersession or authority from recency. - Use already-returned evidence for dedupe. If a likely duplicate exists, open it through the Runtime boundary and ask whether to supersede it or create a distinct artifact.
- Preview the proposed artifacts and wait for
y, edits, orskip. Nothing is canonical before this acceptance. - For each accepted artifact, render its complete Markdown body to a temporary file
under
tmp/and call exactly one domain command;{artifact-file}is that file, and{artifact-type},{title},{topic}, and{workstream}are the accepted artifact's type, title, topic, and workstream:
bash bin/knowledge.sh create \
--type '{artifact-type}' \
--title '{title}' \
--input '{artifact-file}' \
--topic '{topic}' \
--workstream '{workstream}'
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.
- 24d ago Changed · -594 lines · +5 tokens per session a228e6fddeb4
- 1mo ago First seen · 666 lines · 52 tokens per session scan A 2b34387ae2f4
reflect is a skill published in the GitHub repository egregore-labs/egregore (293 stars, last pushed 9d ago), licensed MIT. It adds 57 tokens to every session and 753 once invoked, about $0.0002 per session on Opus 5.5. 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
mnemon
Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle.
mnemon
Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle.
durable-session-state
Persist plans, scope decisions, evidence, and reviewer/critic verdicts to durable files during long or multi-phase tasks so work survives context compaction, session resumes, and handoffs. Use for swarm-mode tasks, before context grows large, when recording approval gates, and when resuming after compaction or a…
mnemon
Persistent memory for MiniMax Code. Recall durable context, store important facts and decisions, and link related memories with the mnemon CLI.
brain-ingest
The process for digesting a conversation, document, or research result, classifying it, and writing it down as brain content (a root-page update or a new/updated page) through the brain CLI.
save-learning
Saves user instructions as persistent learnings for future sessions. Use when the user says 'remember this', 'always do X', 'from now on', 'never do Y', or gives any instruction they want persisted across sessions. Proactively suggest when the user states a preference, convention, or rule they clearly want followed in…