Borrowing it
Nothing to install: this file belongs to sabbour/agentweaver. 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/sabbour/agentweaver/dev/.github/skills/reflect/SKILL.mdgit clone --depth 1 https://github.com/sabbour/agentweaverWrote 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/sabbour/agentweaver/reflect)<a href="https://agentmods.dev/skills/sabbour/agentweaver/reflect"><img src="https://agentmods.dev/badge/skills/sabbour/agentweaver/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/sabbour/agentweaver/reflect"><img src="https://agentmods.dev/badge/skills/sabbour/agentweaver/reflect.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00066 | $0.01711 |
| Opus 5.5 | $0.00026 | $0.00684 |
| Sonnet 5.5 | $0.00013 | $0.00342 |
| Haiku 4.5 | $0.00007 | $0.00171 |
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 1mo 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.
This is a copy
100% identical to reflect — 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 — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reflect Skill
Critical learning capture system for Squad. Prevents repeating mistakes and preserves successful patterns across sessions.
Analyze conversations and propose improvements to squad knowledge based on what worked, what didn't, and edge cases discovered. Every correction is a learning opportunity.
Integration with Squad Architecture
Reflect complements existing Squad knowledge systems:
.squad/agents/{agent}/history.md— Permanent learnings from completed work (append-only; each agent updates their own file; Scribe propagates cross-agent updates).squad/decisions.md— Team-wide decisions that all agents respectreflectskill — Captures in-flight learnings from conversations that may graduate to history.md or decisions.md
Workflow:
- Use
reflectduring work to capture learnings - At session end, review captured learnings
- Promote HIGH confidence patterns → lead agent for decision.md review
- Promote agent-specific patterns →
{agent}/history.mdupdates
Triggers
🔴 HIGH Priority (Invoke Immediately)
| Trigger | Example | Why Critical |
|---|---|---|
| User correction | "no", "wrong", "not like that", "never do" | Captures mistakes to prevent repetition |
| Architectural insight | "you removed that without understanding why" | Documents design decisions (Chesterton's Fence) |
| Immediate fixes | "debug", "root cause", "fix all" | Learns from errors in real-time |
🟡 MEDIUM Priority (Invoke After Multiple)
| Trigger | Example | Why Important |
|---|---|---|
| User praise | "perfect", "exactly", "great" | Reinforces successful patterns |
| Tool preferences | "use X instead of Y", "prefer" | Builds workflow preferences |
| Edge cases | "what if X happens?", "don't forget", "ensure" | Captures scenarios to handle |
🟢 LOW Priority (Invoke at Session End)
| Trigger | Example | Why Useful |
|---|---|---|
| Repeated patterns | Frequent use of specific commands/tools | Identifies workflow preferences |
| Session end | After complex work | Consolidates all session learnings |
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.
- 1mo ago First seen · 230 lines · 66 tokens per session scan A a844dcf82122
reflect is a skill published in the GitHub repository sabbour/agentweaver (7 stars, last pushed today), licensed MIT. It adds 66 tokens to every session and 1,711 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to reflect, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
wiki-ingest
Use when an operation issue asks to ingest a captured raw/ source into the LLM Wiki, or the user says "ingest ". Create durable source, entity, concept, synthesis, index, and log pages; use paperclip-distill for Paperclip bundles.
claude-compaction-restore
Use when a Claude Code session is about to compact, has just compacted, reached its context limit, resumed after /compact, or must rebuild its working picture of a long-running seat from its own restore map, its JSONL transcript and the files it touched.
retiring-and-inheriting-a-seat
Use when you are a sitting agent near your context threshold (85%) and a PLANNED seat transition is due — retire deliberately and hand your seat to a fresh successor primed from a packet, rather than let compaction degrade you. Covers the handover packet, the append-only lineage ledger (one row per tenure)…
session-compaction-and-restore
Use when reasoning about what survives compaction/context-loss/restart/seat-refresh, designing a high-fidelity restore packet, or distinguishing native runtime resume vs fork vs artifact-backed mental-model rebuild. Covers the 4 failure modes that prevent honest restore (compacted seat drops hot potato; restore packet…
memory
Persist important outcomes from this step to long-term storage with automatic forgetting curve.
cross-channel-history-retrieval
A skill for searching the original messages from earlier chat sessions and channels when the current conversation does not contain enough history.