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kata

Agentic engineering katas: proven prompt/loop/tooling patterns from JM Labs. Topics: adaptive-investigation, builtin-tool-selection, confidence-stratified-sampling, context-dilution-mitigation, critical-self-correction, custom-commands-skills, defensive-structured-extraction, deterministic-agent-loop, false-positive-criteria, fewshot-edge-calibration, headless-code-review, hierarchical-claude-memory, hub-and-spoke-isolation, human-handoff-protocol, independent-reviewer-multipass, mcp-server-configuration, mcp-structured-errors, message-batch-processing, multiagent-error-propagation, multipass-prompt-chaining, path-conditional-rules, persistent-scratchpad, plan-mode-exploration, posttooluse-normalization, prefix-caching, pretooluse-guardrails, provenance-preservation, session-resume-fork, tool-description-quality, validation-retry-feedback.

SKILL.md
Quality
Evals
Security

kata

Router skill: one entry, 30 agentic-engineering playbooks. Resolve topic, Read EXACTLY ONE playbook from routes:, apply it. [DOC]

When to use

Trigger when the request maps to a known agentic pattern — building a Claude agent loop, MCP server, hook, structured extraction, code-review harness, memory hierarchy, multi-agent topology, or prompt/sampling/context tactic — and you want the proven JM Labs recipe instead of improvising. [INFERENCIA] Do NOT use as a generic chat or to answer questions that no playbook covers; if no topic fits, say so and route the user elsewhere rather than guessing. [DOC]

Inputs

  • topic (required): one of the 30 routes: keys. Infer from the request; ask only when two topics are genuinely plausible. [DOC]
  • depth (default quick): quick → essentials + the validation gate only; deep → apply exhaustively, verifying at each step. [DOC]

Procedure

  1. Map request → topic. If ambiguous, present the 2 closest keys and ask. [DOC]
  2. Read EXACTLY ONE playbook (its routes: path). Never load the whole cluster — that dilutes context and defeats hub-and-spoke isolation. [INFERENCIA]
  3. Execute along the spine: Discover → Analyze → Execute → Validate. [DOC]
  4. Apply the playbook's own acceptance criteria before declaring done. [DOC]

Validation gate (acceptance)

  • Exactly one playbook was read; topic matches the user's actual intent. [DOC]
  • Output follows the chosen playbook's structure, not improvised prose. [DOC]
  • Every non-obvious claim carries an evidence tag from the kit (Alfa/bracket) family per ../../references/verification-tags.md — never mix tag families. [DOC]
  • Constitution v6.0.0 gates honored: enforcement, evidence tags, script-first (prefer a script over manual steps when one exists). [DOC]
  • Score the result with assets/quality-rubric.json and run assets/routing-checklist.md before declaring done (see assets/README.md). [DOC]

Anti-patterns

  • Loading several playbooks "to compare" — pick one; re-route if wrong. [DOC]
  • Guessing a topic silently when the request is ambiguous. [DOC]
  • Answering from memory of a pattern instead of reading its current playbook — recipes drift; the file is the source of truth. [INFERENCIA]
  • Emitting quick depth but skipping the validation gate. [DOC]

Self-correction

If mid-task the evidence contradicts the chosen topic (wrong failure mode, the playbook's preconditions don't hold), STOP, name the mismatch, and re-resolve topic — do not force-fit the original playbook. [INFERENCIA]

Repository
JaviMontano/jm-adk-beta
Last updated
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