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 skills/mubit-ai/claude-plugins/recallnpx skills add mubit-ai/claude-plugins --skill recallgit clone --depth 1 https://github.com/mubit-ai/claude-pluginsWrote 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/mubit-ai/claude-plugins/recall)<a href="https://agentmods.dev/skills/mubit-ai/claude-plugins/recall"><img src="https://agentmods.dev/badge/skills/mubit-ai/claude-plugins/recall.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 | $0.00037 | $0.00568 |
| Opus 5 | $0.00018 | $0.00284 |
| Sonnet 5 | $0.00007 | $0.00114 |
| Haiku 4.5 | $0.00004 | $0.00057 |
Grade A, and why
recall 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 6d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Relevant memory was already injected at the top of this turn by the Mubit recall hook. Read it before searching. Most of the time you do not need this skill.
When you do:
- Issue one broad
mubit_recallcall. Not three narrow ones. - Read the evidence. If it answers the question, stop.
- Only if the first call returned nothing usable, issue one reformulated call.
Never fan out into parallel searches across sub-topics. Mubit retrieval is hybrid (semantic + lexical + recency + graph); one well-formed query beats four keyword slices at a quarter of the latency. Two calls is the ceiling.
Cite what you use by its reference_id, and call mubit_outcome with those entry_ids
when recalled memory turns out to be right or wrong. That feedback is what makes the next
recall better.
Writing the query
Query with the question, not with keywords. "Why does the drain hook retry twice on a 5xx" retrieves better than "drain retry 5xx", because the semantic half of the hybrid index has something to match on and the lexical half still catches the identifiers. Include the identifiers you already know — file names, symbol names, error strings — inside the sentence rather than instead of it.
A reformulation is a different concept, not a synonym. If "auth failed on ingest" returned nothing, "401 from the control plane" is a reformulation; "authentication failure ingest" is the same query with the words shuffled and will return the same nothing.
When two calls return nothing
Say so and move on. Empty is a real answer: it means nothing about this was ever captured,
and a third query will not invent it. If the answer you then work out by hand is worth
keeping, save it with /mubit-memory:remember so the next session's recall is not empty
too.
Deep searches belong to the subagent
If the question genuinely needs several angles — "what do we know about X" across an
unfamiliar area — invoke @mubit-memory:mubit-recall instead. It runs the same searches in
an isolated context and returns a synthesis, so the raw evidence never lands here.
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.
- 6d ago First seen · 50 lines · 37 tokens per session scan A 4348017051a8
recall is a skill published in the GitHub repository mubit-ai/claude-plugins (13 stars, last pushed yesterday), licensed Apache-2.0. It adds 37 tokens to every session and 568 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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