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/samibs/skillfoundry/recallnpx skills add samibs/skillfoundry --skill recallgit clone --depth 1 https://github.com/samibs/skillfoundryWrote 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/samibs/skillfoundry/recall)<a href="https://agentmods.dev/skills/samibs/skillfoundry/recall"><img src="https://agentmods.dev/badge/skills/samibs/skillfoundry/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 | $0.00011 | $0.01159 |
| Opus 5 | $0.00005 | $0.00580 |
| Sonnet 5 | $0.00002 | $0.00232 |
| Haiku 4.5 | $0.00001 | $0.00116 |
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 2d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/recall — Layered Knowledge Recall
Progressive disclosure search across the memory bank. Three modes: index, preview, full.
Usage
/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 entries
/recall --full id1,id2 Show complete entries with all fields
How It Works
Step 1: Index Mode (default)
When you run /recall "query", search all memory_bank/knowledge/*.jsonl files and return a compact index:
| ID | Type | Score | Weight | Content |
|---|---|---|---|---|
| abcdef12 | decision | 130 | 0.9 | "Standalone agentic loop with zero React deps..." |
| 12345678 | fact | 85 | 0.7 | "Pipeline engine is 6-phase: IGNITE→PLAN→FORGE..." |
Scoring (matches semantic-search.sh algorithm):
- Exact phrase match: +100
- Individual word match (>2 chars): +10 per word
- Type field match: +20
- Weight bonus: +10 * weight
- Tags match: +5 per word
Filters (combinable):
--type=decision|fact|error|preference|pattern--min-weight=0.7(0.0 to 1.0)--since=7d|30d|4w|2026-03-01--tags=auth,security(match any)--limit=10(default: 20)
Max 20 results. Total output: ~400 tokens.
Step 2: Preview Mode
After seeing the index, selectively expand entries:
/recall --preview abcdef12,12345678
Returns first 200 chars of content + metadata (type, weight, tags, created date). Total output: ~600 tokens.
Step 3: Full Mode
For entries you need complete detail:
/recall --full abcdef12
Returns complete canonical entry with all fields (content, tags, weight, lineage, reality_anchor, context).
Implementation
The search engine is sf_cli/src/core/layered-recall.ts with three functions:
recallIndex(query, workDir, filters)— compact search resultsrecallPreview(ids, workDir)— content summariesrecallFull(ids, workDir)— complete entries
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.
- 2d ago First seen · 102 lines · 11 tokens per session scan A d624b0cfcf6e
recall is a skill published in the GitHub repository samibs/skillfoundry (12 stars, last pushed today), licensed MIT. It adds 11 tokens to every session and 1,159 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 2026-09-03.
Other skills, from other repositories
memorix-memory
Use when prior workspace context, past decisions, solved bugs, handoff state, or durable project knowledge would help a coding task.
memorix
Use when Claude Code needs Memorix shared memory, reasoning, Git Memory, mini-skills, session handoff, orchestration coordination, or integration troubleshooting.
memorix-mini-skills
Use when durable project knowledge, gotchas, workflows, or repeated fixes should become reusable agent guidance instead of ordinary memory.
memorix-reasoning
Use when a technical decision, trade-off, rejected alternative, architecture rationale, or design risk should be recorded or recovered.
memorix-sessions
Use when resuming work, preparing handoff context, binding an HTTP control-plane project, or deciding whether sessionstart is useful.
memorix-git-memory
Use when the task depends on commit history, what changed, when a fix shipped, or linking engineering evidence to reasoning memory.