agentleFS
tikalktikalk/adlc-team-skills/skills/team/team-discover/SKILL.md

team-discover

Skill145 starsChanged 21 days agoMITView on GitHub

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.

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 1 is distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Use /team-discover when you want a structured discovery table with explicit relevance assessments — for example, when starting a complex …

    line 15
  2. Distinctive:

    Read full module bodies for High-relevance entries.

    line 36
  3. Very specific:

    If no CDR index was injected at session start: report Searched 0 CDRs — index not injected (unconfigured project or hook failure), reading …

    line 48
  4. Very specific:

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

    line 52

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.