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/mburdo/knowledge_and_vibes/recallnpx skills add Mburdo/knowledge_and_vibes --skill recallgit clone --depth 1 https://github.com/Mburdo/knowledge_and_vibesWrote 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/mburdo/knowledge_and_vibes/recall)<a href="https://agentmods.dev/skills/mburdo/knowledge_and_vibes/recall"><img src="https://agentmods.dev/badge/skills/mburdo/knowledge_and_vibes/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 | $0.00055 | $0.01948 |
| Opus 5 | $0.00028 | $0.00974 |
| Sonnet 5 | $0.00011 | $0.00390 |
| Haiku 4.5 | $0.00006 | $0.00195 |
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 — 362 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Recall — Session Memory
Retrieve relevant history, rules, and anti-patterns from past sessions. Direct execution.
Design rationale: This skill executes directly rather than spawning subagents because memory retrieval is a simple command sequence (~200 tokens), not substantial analytical work. Per Lita research: "Simple agents achieve 97% of complex system performance with 15x less code."
When This Applies
| Signal | Action |
|---|---|
| Starting non-trivial task | Distilled context |
| "What do we know about X?" | Distilled context |
| "How did we do this before?" | Session search |
| Looking for patterns/anti-patterns | Distilled context |
| Stuck on a problem | Deep dive |
| User says "/recall" | Full protocol |
Default: Retrieve context before any non-trivial implementation.
Tool Reference
Commands
| Command | Purpose |
|---|---|
cm context "task" --json |
Distilled rules + anti-patterns |
cm doctor |
Health check |
cass search "query" --robot |
Raw session search |
cass view /path.jsonl --json |
View full session |
cass expand /path -n LINE -C 3 --json |
Expand with context |
cass timeline --today --json |
Today's sessions |
cass index --full |
Rebuild index |
Critical Rule
Always use --robot or --json. Never run bare cass.
Bare cass launches a TUI that will hang AI agents.
Execution Flow
Execute these steps directly. No subagents needed.
Step 1: Distilled Context (Always Start Here)
cm context "{task_description}" --json
Returns:
- Rules — Distilled patterns from past sessions
- Anti-patterns — What NOT to do (and why)
- Suggested searches — Specific CASS queries for more detail
- Historical context — Related past work
Example:
cm context "implement OAuth login" --json
cm context "add new database migration" --json
cm context "refactor the payment module" --json
Step 2: Review and Extract
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 · 362 lines · 55 tokens per session scan A da10f6f37c03
recall is a skill published in the GitHub repository Mburdo/knowledge_and_vibes (44 stars, last pushed 8mo ago), licensed MIT. It adds 55 tokens to every session and 1,948 once invoked, about $0.0003 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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