Borrowing it
Nothing to install: this file belongs to pogorelov-labs/flipper-ble-mcp. 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/pogorelov-labs/flipper-ble-mcp/main/.claude/commands/flipper-learn.mdgit clone --depth 1 https://github.com/pogorelov-labs/flipper-ble-mcpWrote 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/pogorelov-labs/flipper-ble-mcp/flipper-learn)<a href="https://agentmods.dev/commands/pogorelov-labs/flipper-ble-mcp/flipper-learn"><img src="https://agentmods.dev/badge/commands/pogorelov-labs/flipper-ble-mcp/flipper-learn/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/commands/pogorelov-labs/flipper-ble-mcp/flipper-learn"><img src="https://agentmods.dev/badge/commands/pogorelov-labs/flipper-ble-mcp/flipper-learn.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 | $0.00019 | $0.00862 |
| Opus 5 | $0.00010 | $0.00431 |
| Sonnet 5 | $0.00004 | $0.00172 |
| Haiku 4.5 | $0.00002 | $0.00086 |
Grade A, and why
flipper-learn 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 8d 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
You are running the CAPTURE step of the Flipper operating loop — turning what just happened in this
session into durable, re-discoverable KB knowledge so the next run is faster. Work in this repo's KB and
follow its house style (CLAUDE.md). Optional focus hint from the user: $ARGUMENTS
Do this in order; think before writing:
-
Decide if there's anything worth capturing. Scan what this session actually did/learned: a verified workflow, a menu path, a file/log format, a transport quirk, a non-obvious gotcha, a
(verify)you confirmed or newly doubt. If nothing is durable (pure chatter, or all already in the KB), say so and stop — don't manufacture filler. Never capture secrets (card UIDs/keys, EMV PANs, handshakes, credentials) — redact or omit. -
Find the home. Search first:
grep -rl "^domain: <d>" .,uc-index.jsonfor the use case, and the relevant*/README.mdhub. Prefer updating the closest existing doc over creating a near-duplicate. Only create a new doc when the learning is genuinely its own topic. -
Write it KB-style. New or updated doc must have: full ordered frontmatter (title, domain, type, status, summary ≤120 chars, hardware, use_cases, related, tags, last_verified — never omit a key,
[]for empty) → a> **TL;DR —**blockquote → free-form##body →## Open questions / to research→## Sources. Use the skeleton in.claude/skills/flipper/references/capture-template.md. Setlast_verifiedto today. Append(verify)to volatile facts (firmware versions, prices, availability); resolve any(verify)flag this session actually confirmed (and link the doc that confirmed it). -
Cross-link both ways. Add
related:entries in the new doc and in the docs it relates to; add it to the domain hub/README map so it's reachable by browsing, not just by search. An orphan doc is a lost doc. -
Classify SEED vs LOCAL (
.claude/skills/flipper/references/kb-map.md):- General / reusable (capability, method, gotcha, format anyone with the kit would hit) → commit into the SEED tree in place.
- Owner/rig-specific (your exact app inventory, personal setup, private targets) → put under
kb-local/(the gitignored overlay), not the seed tree. - If a
kb-local/learning later proves general, promote it: generalize, move into SEED, and flag it for a PR back upstream ("gold").
-
Rebuild the generated maps. Run
python3 build-kb-index.py. Verify the new/updated doc appears inllms.txt, inuc-index.jsonunder its UC(s), and in the README index. Never hand-edit those generated files. -
Report. Summarize: what was captured, where it lives (path + SEED/LOCAL), which
(verify)flags moved, what cross-links/hub entries were added, and any "gold" worth a PR. Note follow-ups in the doc's## Open questionsso the next session has a head start.
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.
- 8d ago First seen · 46 lines · 19 tokens per session scan A 6c642540fced
flipper-learn is a command published in the GitHub repository pogorelov-labs/flipper-ble-mcp (0 stars, last pushed 2mo ago), licensed MIT. It adds 19 tokens to every session and 862 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 2026-09-01.
Other commands, from other repositories
sound-performance-live-mix
Live mix plan with redundancy — FOH priorities, per-performer monitor mix, IEM-vs-wedge decision, redundancy plan per critical path, soundcheck protocol. Hearing-health baseline non-negotiable. Refuses single-point-of-failure live mix.
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
eol-report
EOL/EOS risk report — devices, OS versions, and firmware approaching or past end-of-life/end-of-support, prioritized by criticality.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.