agentleFS
ulises-jeremiasulises-jeremias/agent-toolkit/skills/core/dev-companion/SKILL.md

dev-companion

Skill19 starsChanged 2 months agoMITView on GitHub

WHAT — Dev Companion (general): layered companion for client delivery; modes, gates, delegation

We split this skill into the rules it gives an agent

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

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    If engagement triggers match, load the appropriate workspace pack overlay first, then proceed with workflow-generic-project.

    line 22
  2. Distinctive:

    If the user mentions an engagement, ticket prefix, or repo context → load the matching pack from the workspace (overlay) and apply its …

    line 27
  3. Distinctive:

    If unclear → ask before applying L3.

    line 28
  4. Distinctive:

    Do not paste forge or ticket CLI sequences here.

    line 53
  5. Very specific:

    Queued job (optional): only when a local runner is configured.

    line 58

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 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

Dev Companion (WHAT) — general layer (L2)

This skill is the general dev companion for work. It does not replace assistant (orchestrator); it sits above workflows and names what to invoke next.

Language: English for ticket comments, PR text, and user-facing outputs when this companion drives delivery work.

Layering

LayerSkillRole
L1assistantRepo inspection order, conflict resolution, fallback
L2 (this skill)dev-companionCompanion framing: modes, gates, delegation for client work
L3Workspace pack overlayClient/account-specific context loaded from ~/.ai-workspace/packs/

If engagement triggers match, load the appropriate workspace pack overlay first, then proceed with workflow-generic-project. Do not mix multiple workflow drivers on the same task.

Mode selection

  • Default for /client delivery: use workflow-generic-project for phased delivery.
  • If the user mentions an engagement, ticket prefix, or repo context → load the matching pack from the workspace (overlay) and apply its boundaries/gates.
  • If unclear → ask before applying L3.

Delegation (HOW is in other skills)

NeedDelegate to
Discovery, AGENTS conflict handlingassistant
Generic client delivery phasesworkflow-generic-project
Planning / default workflow / validationplanning / development-workflow
Work items, incidents, meetings, decisions, agreements, spikeswork-item, incident, meeting-minutes, decision-log, agreement, spike
Project assessments, evidence maps, technical/management unit scorecardsproject-assessment, project-assessment-evidence, technical-unit-assessment, management-unit-assessment
ClickUpclickup-cli
JiraExternal jira-* pack (jira-assistant router; CLI: jira-as)
ConfluenceExternal confluence-* pack (confluence-assistant router; CLI: confluence-as or confluence)
Draft PR GitHub / GitLabgithub-cli-workflow / gitlab-cli-workflow (for default body when the repo has no template: pr-fallback first)
CI failures (GitHub Actions)gh-fix-ci
Merge / rebase conflictsfix-merge-conflicts
Prose quality before PRunslop
Code slop in diffdeslop
Large change scopeblast-radius
Session learningsworkspace-knowledge-sync
Where to save deliverables + human reviewoutput-handshake
UI depthfigma / figma-implement-design
Workstation healthtriage

Do not paste forge or ticket CLI sequences here.

Operating modes

  • Interactive (default): IDE session; user steers each step.
  • Queued job (optional): only when a local runner is configured; see ~/.local/share//dev-companion/README.md (installed from chezmoi) and references/LOOP_GUARDRAILS.md.

The queue worker is mandatory infrastructure (installed by workstation). The workspace (~/.ai-workspace) is optional — it provides project-aware wrappers, job templates, and knowledge base integration. When both are present, the runner automatically enriches LLM prompts with workspace context (projects.yaml, projects/, knowledge/todos/).

LLM policy gate (client engagements)

Before queueing background jobs for a client repo, confirm the active LLM policy with devcompanion llm-status. If the engagement requires a single AI account (e.g. only the customer's Anthropic key), the workstation/pack must set DOTS_WORKSTATION_DEVCOMPANION_LLM_ALLOWLIST and DOTS_WORKSTATION_DEVCOMPANION_LLM_STRICT=1 so the runner fails closed instead of falling back to OpenCode. For Cursor/Copilot-only engagements, prefer run-once --no-llm (skeleton plan) plus IDE-driven execution. Full reference: docs/DEV_COMPANION_LLM.md.

Checklist

  • L3 not needed; if needed, user confirmed engagement context
  • assistant discovery pass before large edits
  • workflow-generic-project phases and gates when doing generic client delivery
  • Tool skills used for all CLI operations

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