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SKILL verified MIT Self-run

Recall

skill-abysscn-oh-my-dag-recall · by AbyssCN

Memory layer active recall: when reasoning/writing/decisions stall, the agent proactively queries the memory store instead of waiting for a hook to fire. Fills the blind spots left by passive (hook-triggered) consumption. Trigger: /recall / recall / there should be precedent / 查历史 / 翻一下记忆 / 以前怎么做的. Skip: file grep / call chains (/graph) / library docs (context7) / git history (git log).

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Install

$ agentstack add skill-abysscn-oh-my-dag-recall

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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16d ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

/recall — Memory Layer active recall

> Active consumption of the memory layer, filling the blind spots of hook-triggered passive recall.

When to use

When you proactively want past context (not a hook firing automatically):

  • Stuck while writing a plan/spec — wondering "how did we decide similar cases before"
  • Design choice — "X or Y" and want to see the historical rationale
  • Cross-module reuse — "which module solved a similar problem before"
  • Methodology query — "what is our standard here"
  • Historical lesson query — "have we hit this pitfall before"

Not for:

  • Literal in-file search → grep
  • Function call chains → /graph what-uses / refs
  • Third-party library docs → context7
  • Git commit history → git log

Input

/recall 
/recall  --k 5            # default k=5
/recall  --kind decision  # filter by source kind
/recall  --path docs/plan # path filter

`` can be:

  • A natural-language query: auth cross-tenant isolation
  • Keywords: report pipeline release gate
  • Filename + keywords: dashboard-overview.ts feature flag

Workflow

Step 1 — Pick K and filter

K defaults to 5 (a fuller view on active recall).

If `` involves:

  • decision/proposal → add --kind decision
  • standard/spec → add --kind standards
  • failure/pitfall → add --kind error,journal
  • file history → add --path

Step 2 — Call the retrieve CLI

npx tsx .claude/memory/scripts/retrieve.ts "" --k 5 --format briefing

With a path filter (decisions generally live under docs/plan/ or docs/spec/):

npx tsx .claude/memory/scripts/retrieve.ts "" --k 5 --format briefing --path-filter "docs/(plan|spec)/"

With an arbitrary path filter:

npx tsx .claude/memory/scripts/retrieve.ts "" --k 5 --format briefing --path-filter ""

Step 3 — Present + self-assess

Output the retrieve briefing (top-5 source path + breadcrumb + short preview).

Then self-assess relevance:

  • which one directly answers the topic
  • which one is only tangentially related
  • which one is irrelevant

Output format

### 💾 Relevant Memory (top-5)

1. **[decision]** PLAN-dashboard-overview.md — dashboard overview pipeline...
   `docs/plan/PLAN-dashboard-overview.md` · 0d old

2. **[standards]** ENGINEERING-STANDARD.md — engineering invariants + state machine...
   `docs/standards/ENGINEERING-STANDARD.md` · 7d old

...

Domain-first self-check

The memory layer is a meta-layer, not a domain. /recall usage limits:

  • ✅ Before/during plan/spec writing: high value, prevents reinventing the wheel
  • ✅ At decision moments: historical decision rationale
  • ⚠️ Don't use it for exploratory idle browsing — a slow retrieve doesn't beat grep
  • ❌ Don't use it as a retrospective substitute — a retro reads git, not memory chunks

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.