tikalk/adlc-team-skills

team-discover

Use when explicit manual re-discovery of team context modules is wanted beyond the injected CDR index (/team-discover) — produces a structured match table with relevance assessments.

View source

How to use

  1. Copy the installation command and review the source package before installing it in your own agent environment.
  2. Check the source document for required tools, credentials and supported hosts.
  3. Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/tikalk/adlc-team-skills --skill team-discover

Before you start

  • Installation does not include a model subscription, API allowance or permission to access your files.
  • Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document

Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.

team-discover

Overview

The CDR index is injected into the system prompt at session start by team-boot. The LLM natively matches CDR descriptors against the current task and reads full module bodies on demand. This native matching happens per prompt without invoking this skill.

Use /team-discover when you want a structured discovery table with explicit relevance assessments — for example, when starting a complex feature or verifying which directives apply.

Relationship to team-boot

team-boot is the session bootstrap: it injects the CDR index into the system prompt via the session_start event hook. Per-prompt discovery matching is native — the LLM matches the injected CDR index against the current message on its own, so team-boot does not invoke this skill as part of its bootstrap loop.

/team-discover is user-invoked: run it when you want an explicit, structured re-scan with a relevance-rated table (complex features, audits, or verifying which directives apply). It is not required for normal operation.

Process

  1. Extract domain, technology, patterns, and actions from the task.
  2. Scan the CDR index for matching entries.
  3. Assess relevance: High / Medium / Low.
  4. Read full module bodies for High-relevance entries.
  5. Output:
IDModuleTypeDescriptorRelevance
CDR-2026-003context_modules/personas/admin.mdPersonaAdmin personaHigh
  1. Include PDR/ADR/ChDR matches from project indexes if relevant.
  2. Include: _Searched N CDRs, M PDRs, K ADRs, C ChDRs, J matches found._

Absent Context

If no CDR index was injected at session start: report Searched 0 CDRs — index not injected (unconfigured project or hook failure), reading workspace memory directly, proceed against docs/adlc/memory/ on disk, and continue the task. Never present on-disk fallback rows as injected context. Recovery: run /team-diagnose.

Unconfigured projects

If team AI directives are not configured, invoke team-setup.

Related by task

from this repository

More skills

All skills