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.
git clone --depth 1 https://github.com/grcengineering/companionWrote 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/grcengineering/companion/recall)<a href="https://agentmods.dev/commands/grcengineering/companion/recall"><img src="https://agentmods.dev/badge/commands/grcengineering/companion/recall/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/grcengineering/companion/recall"><img src="https://agentmods.dev/badge/commands/grcengineering/companion/recall.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 | $0.00012 | $0.00138 |
| Opus 5.5 | $0.00005 | $0.00055 |
| Sonnet 5.5 | $0.00002 | $0.00028 |
| Haiku 4.5 | $0.00001 | $0.00014 |
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 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.
What it actually says
Recall Command
Use when the learner wants to test memory or revisit prior concepts.
Flow
- Pick three related concepts.
- Ask one question at a time.
- Let the learner answer before giving feedback.
- Grade briefly as correct, partial, or not yet.
- Schedule the next review.
Boundary
Quiz concepts and reasoning, not the compliance posture of a real system.
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 · 27 lines · 12 tokens per session scan A c272eafb5764
recall is a command published in the GitHub repository grcengineering/companion (34 stars, last pushed 5mo ago), licensed MIT. It adds 12 tokens to every session and 138 once invoked, about $0.0000 per session on Opus 5.5. 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.
Other commands, from other repositories
evidence-examples
Get evidence examples for FedRAMP compliance.
list-controls
List NIST controls from FedRAMP FRMR documents.
compare-versions
Compare two versions of an FRMR document.
control-coverage
Analyze NIST control family coverage.
control-requirements
Get all requirements for a NIST control.
filter-impact
Filter KSI items by impact level (low, moderate, high).