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/deep-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/deep-reflect)<a href="https://agentmods.dev/skills/egregore-labs/egregore/deep-reflect"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/deep-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/deep-reflect"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/deep-reflect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 106 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 | $0.00049 | $0.03457 |
| Opus 5 | $0.00024 | $0.01729 |
| Sonnet 5 | $0.00010 | $0.00691 |
| Haiku 4.5 | $0.00005 | $0.00346 |
Grade A, and why
deep-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 10d 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep research over org memory — ask a question, get a verified, cited synthesis of what the org collectively knows, including what it doesn't.
Multi-hop, multi-agent research over memory/ (plus the graph, when connected). Waves of parallel readers hop a lead ledger until saturation; a skeptic pass kills every claim it cannot re-find in the cited file. /reflect captures user thought; /deep-reflect researches what the org already knows.
Pipeline: deep-reflect v4 · 2026-07-11 · thin entry + sibling contracts (RESEARCH.md, ROLES.md, REPORT.md).
When to invoke
User says: "deep dive on X", "what do we know about X", "what does the knowledge base say about X", "research what we know about X", "what's the org's position on X", "cross-reference this", "analyze this against what we know", "connect the dots between X and Y"
Not this: web sources → out of scope (this skill researches memory, not the web) · one-shot recall ("what did we decide about X") → /search · capture a new insight → /reflect · ask people, not documents → /harvest · private thought → /note · track the open question itself → /quest
Arguments: $ARGUMENTS (Optional: [question or insight] [--brief|--deep] [--quest ] [--no-capture] [--resume ])
Saves through the capture gate. A Save verdict runs the full /save flow — no separate /save after.
Modes
| Mode | Job | Extra output |
|---|---|---|
| question (default) | Answer a research question from memory | — |
| cross-ref | v2's job: situate one insight against the corpus | verified RELATES_TO/TENSION_WITH edge proposals (connected) |
Both modes write reports to memory/knowledge/research/ — except --brief and probe-collapsed sparse runs, which default to terminal-only output with a two-option Save/Skip gate (Save writes the standard file). Depth bands are orthogonal; the default is dynamic, set by the Stage-0 corpus probe:
| Band | Waves | Docs read | Wall clock |
|---|---|---|---|
--brief |
1 | ~8 | ~1-2 min |
| standard | ≤3 | ~24 | ~3-5 min |
--deep |
≤5 | ~45 | ~6-10 min |
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 155 lines · 49 tokens per session scan A 04e0b8c20c0e
deep-reflect is a skill published in the GitHub repository egregore-labs/egregore (289 stars, last pushed 6d ago), licensed MIT. It adds 49 tokens to every session and 3,457 once invoked, about $0.0002 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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Turn on Rekal memory in the current repository by running rekal init. Use when the user asks to initialize or set up Rekal here, or when a rekal command reported the repository is not initialized. Once per repository. Do not offer this merely because a repo lacks a .rekal/ store — most repos do not want one.
install
Install the Rekal binary on this machine. Use when rekal is not on PATH — a command reported command not found — or when the user asks to install Rekal. Once per machine, not per repository; to set up a repo that already has the binary, use the init skill instead.
atomic-wiki
Conversational wiki and capture-bucket routing. Fires when the user wants a place, space, or folder for notes, research, tickets, raw dumps, or knowledge capture — checks the block in /.claude/CLAUDE.md; if the cwd is under a registered realm, creates the folder as a bucket via atomic wiki bucket add rather than a…
remem
Use when the user asks Codex to recall prior project context, save durable decisions or bug fixes, inspect remem memory health, or activate remem automatic memory hooks from the Codex plugin.