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 commands/everyone-needs-a-copilot/claude-copilot/reflectgit clone --depth 1 https://github.com/Everyone-Needs-A-Copilot/claude-copilotWrote 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/commands/everyone-needs-a-copilot/claude-copilot/reflect)<a href="https://agentmods.dev/commands/everyone-needs-a-copilot/claude-copilot/reflect"><img src="https://agentmods.dev/badge/commands/everyone-needs-a-copilot/claude-copilot/reflect.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 5.1 | $0.00000 | $0.01020 |
| Opus 5 | $0.00000 | $0.00510 |
| Sonnet 5 | $0.00000 | $0.00204 |
| Haiku 4.5 | $0.00000 | $0.00102 |
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 yesterday.
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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reflect Command
Review the memory captured this session — decisions, lessons, and context — surface gaps or errors in reasoning, and store any corrections as memory entries.
Overview
/reflect is the end-of-session review step on top of the cc memory CLI. It
replaces the MCP-era correction-detection system (the correction_* tools and the
pending/approved/rejected queue were removed in the CLI migration).
/reflect does not:
- Auto-detect correction patterns in user messages (the MCP pattern engine is gone).
- Maintain a pending/approved/rejected queue.
- Route corrections to skill or agent files automatically.
To update a skill or agent from a correction, edit the SKILL.md / agent file
directly or delegate to @agent-me.
Arguments
- No arguments: review recent
lesson,decision, andcontextentries. --type <lesson|decision|context|reference>: review only one entry type.<search terms>: review entries matching a topic (usescc memory search).
Step 1: Gather Memory
# Default review: recent lessons, decisions, and context (project scope)
cc memory list --type lesson --json
cc memory list --type decision --json
cc memory list --type context --json
# Single type (when --type is passed)
cc memory list --type <type> --json
# Topic review (when search terms are passed)
cc memory search "<terms>" --json
Read fuller content for any entry by UUID (full or prefix match):
cc memory get <entry-id>
Step 2: Present a Review Dashboard
Format the gathered entries as a compact review (newest first; truncate long content to ~100 chars). Example:
## Session Reflection
**Stored this session:** 3 lessons · 2 decisions · 1 context
### Lessons
- [a1b2c3] "Use async/await instead of callbacks in Express middleware…"
- [d4e5f6] "Yarn workspaces, not npm — earlier assumption was wrong"
### Decisions
- [g7h8i9] "Adopt FTS5 keyword search; defer semantic embeddings"
### Context
- [j0k1l2] "Auth service runs behind Cloudflare Access in staging"
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.
- yesterday First seen · 138 lines · 0 tokens per session scan A 91729ddc31a3
reflect is a command published in the GitHub repository Everyone-Needs-A-Copilot/claude-copilot (13 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,020 tokens. 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 2026-09-04.
Other commands, from other repositories
gohm
Persona: You are the Knowledge Harvester -- you extract signal from noise, turning session work into durable organizational memory. Reflection Protocol: See agents/reflection-protocol.md for reflection requirements.
memory
You are the Memory Curator, the guardian of NASAB Pillar 5: Permanent Memory. You ensure that nothing is ever deleted from the knowledge base - only the retrieval path changes. You are the librarian of an infinite library where every book remains on the shelf, but some are easier to find than others.
context
You are the Context Manager, responsible for monitoring and optimizing context usage during long implementation sessions. You help prevent context overflow and maintain efficiency.
recall
/recall "query" Search and show compact index /recall "query" --type=decision Filter by entry type /recall "query" --min-weight=0.7 Filter by minimum weight /recall "query" --since=7d Filter by recency /recall "query" --tags=auth,security Filter by tags /recall --preview id1,id2,id3 Show content summaries for specific…
INFO
Каждый новый терминал = новая сессия = пустой контекст. Агент не знает по какому проекту работаем, какой стек, какие серверы, где деплой, какие активные задачи. Пользователь вынужден на каждом старте перечислять одно и то же — теряется время и мысль.
vulyk-gc
Memory garbage collection - consolidate learnings, prune stale pointers, clean snapshots.