agent-health
Reads production/traces/agent-metrics.jsonl and displays a per-agent performance summary table for the current or a specified session. Highlights agents with…
Turns real agent failures, repeated prompts, team-specific workflows, and durable project lessons into better SDD skills or memory entries. Use when the user asks to create/update/refine skills, extract reusable lessons, improve skill routing, encode team process, or save
$ npx -y skills add tranhieutt/software_development_department --skill learner --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/learnerContext preview
The summary Claude sees to decide when to auto-load this skill.
Turns real agent failures, repeated prompts, team-specific workflows, and durable project lessons into better SDD skills or memory entries. Use when the user asks to create/update/refine skills, extract reusable lessons, improve skill routing, encode team process, or save
name: learner type: workflow description: "Turns real agent failures, repeated prompts, team-specific workflows, and durable project lessons into better SDD skills or memory entries. Use when the user asks to create/update/refine skills, extract reusable lessons, improve skill routing, encode team process, or save patterns for future sessions." argument-hint: "[session summary, failure mode, repeated prompt, or skill improvement request]" allowed-tools: Read, Glob, Grep, Write, Edit, Bash user-invocable: true effort: 3 when_to_use: "Use when a lesson should become durable: after repeated corrections, wrong skill routing, repeated long prompts, team-specific process discovery, or a complex session worth converting into a skill or memory entry."
Convert real SDD usage into durable operating knowledge.
Use this workflow to decide whether a lesson belongs in:
This workflow adopts the Agent Skills guidance that durable skills come from real expertise, project artifacts, execution traces, and repeated refinement. Skills should capture team-specific process and failure modes, not generic best practices or deterministic glue better handled by scripts, hooks, or MCP.
Create or modify a skill only when at least one signal is present:
Do not create a skill for:
Classify the lesson before editing:
| Lesson type | Target | | --- | --- | | Existing workflow missed a rule, edge case, or output shape | Update that skill body | | Existing skill should have fired but did not | Tighten that skill `description` | | Repeated team-specific process forms a coherent unit | Create or update a skill | | Non-obvious caveat tied to a service/library/repo area | Use `annotate` memory | | Broad preference or project operating rule | Update the right Tier 2 memory/doc | | Deterministic repeated operation | Prefer tested script/hook/MCP; skill only orchestrates when needed |
Prefer updating an existing skill over adding a new one when the lesson fits an existing coherent workflow.
1. Gather evidence:
2. Choose the smallest durable target using the Decision table. 3. Edit with progressive disclosure:
4. Tune invocation:
5. Preserve SDD gates:
6. Validate:
Use this shape when a new SDD skill is justified:
--- name: short-action-name type: workflow description: "What this skill does. Use when <specific trigger phrases, task contexts, and boundaries>." argument-hint: "[expected input]" user-invocable: true allowed-tools: Read, Glob, Grep effort: 2 when_to_use: "One sentence matching the description scope for SDD docs and humans." --- # Purpose State the reusable team-specific capability. ## Workflow 1. Do the first required action. 2. Make the context-dependent decision. 3. Verify with a concrete check. ## Gotchas - Add only non-obvious failure modes discovered from real use. ## Output Specify the exact artifact or response shape when consistency matters. ```` ## Completion Output Report: - artifact changed or created, - evidence source that justified it, - validation commands and results, - remaining skill debt or telemetry gap.
Repo: tranhieutt/software_development_department
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