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Trinity

agent-dev Plugin

Development tools for extending existing agents - skills, memory systems, git-backed state, a GitHub Issues development cycle, long-running pipelines, multi-agent orchestration, a shared canonical-data layer, and fleet analysis and migration.

Why Every AI Agent Needs a GitHub Repo

Apr 2026

3 AI Agents Run My Software Development Pipeline

Apr 2026

Installation

/plugin install agent-dev@abilityai

Skills

SkillDescription
/agent-dev:create-playbookCreate a new skill/playbook for the agent
/agent-dev:adjust-playbookModify an existing skill/playbook
/agent-dev:add-memoryAdd a memory system (file-index, brain, json-state, workspace)
/agent-dev:add-git-syncAdd git-as-state hooks - auto-commit on stop, rebase on session start
/agent-dev:add-backlogInstall the full GitHub Issues development cycle into the agent
/agent-dev:backlogView the agent's current GitHub Issues backlog
/agent-dev:claimClaim the next issue - picks the highest-priority todo, marks it in-progress
/agent-dev:autoplanAnalyze a claimed issue before implementing - affected files, changes, risks
/agent-dev:commitCommit changed skill files and close the in-progress issue with traceability
/agent-dev:closeClose the current issue without a commit (use /commit when files changed)
/agent-dev:groomGroom the backlog - label untagged issues, verify priorities, surface stale work
/agent-dev:roadmapStrategic view - open issues grouped by skill area
/agent-dev:sprintHuman-supervised cycle: roadmap → claim → autoplan → implement → commit
/agent-dev:work-loopAutonomous unit of work: pick one issue, execute, close, exit
/agent-dev:planPlan and execute a large multi-session project
/agent-dev:add-pipelineScaffold a long-running multi-stage pipeline inside the agent
/agent-dev:add-pipeline-instanceAdd an instance (tenant / zone / case) to an existing pipeline
/agent-dev:add-pipeline-stageAppend a stage to an existing pipeline definition
/agent-dev:validate-pipelineLint a pipeline.yaml - schema, DAG acyclicity, referenced skills
/agent-dev:add-orchestratorMake the agent a system-aware orchestrator - discover the fleet, compose systems, route and fan out work; --check reports installed-vs-bundled drift before you overwrite
/agent-dev:add-canonGive the agent a shared canonical-data layer - a fleet canon repo with publish/consume/reconcile/doctor skills
/agent-dev:add-canon-lintInstall deterministic consistency linting into the fleet's canon repo - two-zone schema, CI on every push
/agent-dev:add-project-managementInstall cross-actor project management - GitHub Issues as the source of truth, an approval-ready completion lattice, and a project steward
/agent-dev:agent-fleet-analysisScan directories of agents in any paradigm - score maturity, map gaps to marketplace skills, emit a report + work order
/agent-dev:agent-fleet-migrateExecute the fleet-analysis work order - non-destructive migration into a verified Claude Code fleet

Fleet-scale skills

The last five are about a set of agents rather than one: Canon (add-canon, add-canon-lint) gives a fleet a shared, citable source of truth on plain git; Project management (add-project-management) installs a cross-actor task model on GitHub Issues; Fleet analysis and migration (agent-fleet-analysis, agent-fleet-migrate) are a pair that audits agents in any paradigm and then carries out the resulting work order. Each is described in its own section below.

Memory Systems

Add persistent memory to agents via /agent-dev:add-memory:

SystemPurposeUse When
file-indexWorkspace file awareness and searchAgent needs to know what files exist
brainZettelkasten-style knowledge graphAgent builds connected notes over time
json-stateStructured JSON state with jq updatesAgent tracks counters, config, or structured data
workspaceMulti-session project trackingAgent works on long-running projects

Memory systems are copied directly into the agent - no plugin dependency at runtime.

Git Sync (git-as-state)

/agent-dev:add-git-sync

Installs hooks that treat the agent's own repository as durable memory:

Auto-commit on Stop - work-in-progress is committed when a session ends
Rebase on SessionStart - each session begins from the latest remote state
Snapshot on PreCompact - state is preserved before context compaction

This gives agents durable cross-session memory through their repo, complementing Trinity's GitHub Sync on the platform side.

Playbook Development

Create a New Playbook

/agent-dev:create-playbook

Guides through purpose (what the playbook accomplishes), triggers (when it should run), steps (the workflow steps), and state (what data it reads/writes).

It picks a complexity tier and generates from a bundled template:

TierShapeTemplate
1 - Simple skillStateless procedure, no persistent datasimple-skill
2 - Stateful skillReads/writes agent state between runsstateful-skill
3 - Full playbookMulti-step, scheduled or delegated workmanual, gated, or autonomous - by automation level

Every generated skill carries a metadata: block with a newest-first changelog and a what's-new banner, and - for anything on a schedule - invokes by slash name so the scheduler message stays a bare call. Playbooks are written to be called: from a single /name [args] line, with inputs declared in argument-hint, running only themselves when invoked by another agent. See Playbook calls for the convention, and the --autonomous run mode any gated playbook needs before it can go on a cron.

Modify an Existing Playbook

/agent-dev:adjust-playbook daily-report

Options: add/remove steps, change automation level, update schedule, fix issues, and make callable by other agents - retrofit an existing skill to the playbook-call rule (declared arguments, one-line invocation, a headless mode if it has gates).

GitHub Backlog Workflow

Add task management via GitHub Issues:

/agent-dev:add-backlog

This installs the full development cycle directly into the agent. After install, the agent has:

/backlog - view current issues
/claim - claim the next issue to work on
/autoplan - analyze the claimed issue before implementing
/commit - commit changes and close the issue with a traceable message
/close - close without a commit
/groom and /roadmap - keep the backlog labeled, prioritized, and surveyable
/sprint - the human-supervised end-to-end cycle
/work-loop - the autonomous variant (below)

Autonomous Work Loop

/agent-dev:work-loop

One bounded unit of work: the agent picks the highest-priority issue, executes it, closes it, and exits. It is designed to be re-invoked - by a Trinity schedule for a steady cadence, or by a Trinity agent loopfor a bounded burst ("drain up to 20 items, stop when the backlog is empty").

Pipelines (long-running multi-stage work)

/agent-dev:add-pipeline

Scaffolds an agent-owned pipeline for work that spans days or weeks (e.g. perception → synthesis → publish → measure): a projects/<slug>/ directory with pipeline.yaml and per-instance state, tick/status/recover/pause/resume skills, a heartbeat schedule that advances stages, and a ~/.trinity/ read surface so Trinity can display pipeline state without owning it.

/agent-dev:add-pipeline-instance - add a tenant/zone/case to an existing pipeline
/agent-dev:add-pipeline-stage - extend the stage DAG
/agent-dev:validate-pipeline - lint the definition (schema, acyclicity, skill references)

A stage can name a local skill or delegate to another fleet agent - agent: <fleet-agent> calls that agent's playbook as one line with --run <pipeline>/<instance>, dispatched asynchronously and polled for its result; such stages skip the local-skill check.

Pipelines are owned by the agent, not by Trinity - the platform only reads the published state. This matches Trinity's agent-defined-pipelines design: no central DAG engine.

Orchestration (multi-agent)

/agent-dev:add-orchestrator

Makes any agent a system-aware orchestrator of other agents. Two modes, picked by whether the fleet already exists: describe and route over an existing fleet (read-only - discover, then orchestrate; no manifest, no deploy) or provision a new system (author the intent, compose a manifest, deploy, then orchestrate). It installs these skills into the agent:

SkillPurpose
/discover-agentsDiscover the fleet (from the live Trinity instance and/or a repo list) into a descriptive fleet/system-map.yaml - including each agent's pipelines and canon declarations
/compose-systemTurn the map into a Trinity system manifest and deploy it; members are declared as github:Org/repo so the fleet is reproducible from source, and a spec-less repo gets a post-deploy /trinity:onboard in-place playbook call
/orchestrateRoute work to the right agent, fan the same task out across several, chain ordered steps, open a room, wire standing event reactions, or roll out an ephemeral agent for a one-off job - via Trinity MCP
/sync-fleet-to-headNon-destructively bring in-scope agents to their GitHub HEAD
/profile-fleetInterview and introspect agents, reconcile reality against the fleet narrative
/fleet-reconcileFold already-verified deltas into every doc surface behind one gate
/project-init, /project-steward (opt-in)The project-management layer: create or adopt a managed project, and an autonomous steward that dispatches labeled work, escalates stalls, ages the operator's open loops, and writes a daily digest

Three conventions run through the whole bundle:

Dispatch is a playbook call. /orchestrate resolves each dispatch to a playbook from the target agent's live skill catalog and sends one line - /<playbook> [args] --run <task_id> - never a prose brief (a freeform brief is the recorded exception). Fire-and-park, never block-and-wait: it subscribes to the target's task-completion event and reports back when the work lands. See Playbook calls.
Standing wiring uses events, not pollers. For “whenever X happens, have Y react”, /orchestrate wires Trinity's pub/sub layer: the source agent's playbook is instructed to emit_event a named domain event, and the reacting agent subscribes itself (subscriptions are self-service, so the setup is dispatched to the subscriber, never wired on its behalf) with a {{payload.field}}-interpolated task. The design rules the platform does not enforce - exact-match event names, keep custom event graphs acyclic (only the built-in task-completion events carry a loop guard), a wake reaches only a running subscriber, interpolated payloads are agent-authored text - are written into the fleet narrative so the wiring stays reviewable. See Event Subscriptions.
Loop closure. A run is not done until the requester has been told the outcome, including failure; work parked on someone outside the fleet is labeled waiting-on:<actor>, aged, and handed back with a drafted follow-up. The agent drafts; the human sends.

Re-running the installer. /agent-dev:add-orchestrator --check is a read-only divergence report - per installed skill it says whether the bundle moved ahead (upgrade available), whether the installed copy was hand-edited (an overwrite would discard it - the diff is shown), or whether the installed copy is aheadof the bundle (a field-hardened copy the marketplace should pull from - an overwrite would be a downgrade). The same comparison runs inside every overwrite prompt when you re-run the installer, so the warning arrives at the moment of decision. It compares only this bundle's own skills and keeps no state on disk.

Gated skills on crons. /sync-fleet-to-head and /profile-fleet ask questions at their decision points; put on a schedule as-is, each run would block on a prompt nobody sees. Both declare a --autonomous run mode - the schedule message is the bare /<skill> --autonomous, and the skill takes the safe default at every gate, never a destructive path, recording anything non-trivial as a needs-attention line. This is the bundle-wide convention every gated-and-scheduled skill follows.

The orchestrator builds on Trinity's existing multi-agent primitives rather than inventing a parallel standard - see System Manifest, Fan-Out, and Rooms. Pipelines are the intra-agent sibling: /orchestrate routes pipeline-shaped work to the agent that owns the pipeline instead of re-sequencing its stages as a chain; canon is the data sibling: reads of published facts are served from the canon repo, writes are dispatched to the owning agent.

Canon (shared canonical data)

/agent-dev:add-canon

Gives any agent a shared canonical-data layer - a fleet-wide canon repo on plain git where each agent owns an agents/<name>/ folder, with conventions (CONVENTIONS.md, CODEOWNERS) instead of a new platform primitive. It installs four runtime skills into the agent:

/canon-publish - commit this agent's own folder in the shared canon repo
/canon-consume - read other agents' published data at a cited ref
/canon-reconcile - scheduled freshness pass over the agent's own folder
/canon-doctor - verify the layer end-to-end (credentials, clone, push permission) from wherever the agent runs

In orchestrator fleets (a fleet/system-map.yaml is present), it can also enroll the mapped agents - all or a subset - into the same canon.

Each agent owns a folder it publishes to and reads other agents' folders at a pinned ref. The layer also carries relations- per-counterpart collaboration memory: each agent keeps one doc per agent it actually works with (working agreements, a capped log of recent events, open threads), reads it before acting on that counterpart's request and appends the outcome before closing the interaction. Each side keeps its own view; a divergence between the pair is a dropped-thread signal, and open threads older than 30 days surface as needs-review rows in the reconcile pass.

/agent-dev:add-canon-lint

The enforcement sibling - run once per fleet against the canon repo itself, not an agent. Seeds a deterministic linter (stdlib-only Python, no LLM), a severity config, and a GitHub Actions workflow that lints every push/PR. It defines the two-zone folder schema: facts.yaml holds purely lintable claims, docs/ holds prose with a linted envelope. Optionally makes the lint a required PR status check; the per-agent gate ships with the add-canon runtime skills (/canon-publish lints before pushing).

Project Management (cross-actor)

/agent-dev:add-project-management

Installs a cross-actor task model on GitHub Issues, with an open → pending-verification → done lattice so work isn't marked complete until it's been verified, and a loop-closure discipline: no loop closes by silence in either direction. Every run ends by stating what is now true, what is waiting on the operator, and what happens next; work parked on someone the system cannot dispatch to (a client, a vendor, a colleague) is labeled waiting-on:<actor>, aged on a 3/7/14-day ladder, listed under Your open loops in the digest, and handed back with a drafted follow-up - the agent drafts, the human sends. See add-project-management for the installed artifacts.

Fleet Analysis & Migration

/agent-dev:agent-fleet-analysis

Scans one or more directories of agents in any paradigm - Claude Code, n8n workflow exports, framework apps (LangChain / CrewAI / AutoGen), or freeform-coded agents. It assesses quality (a fleet maturity score for Claude Code agents, a migration-readiness score for the rest), designs the right fleet architecture (hierarchy, knowledge brain, memory, canon layer), maps every improvement to an installable skill from the abilities marketplace, and generates a PDF report plus a markdown twin that agents can execute as a work order. Value-first - useful whether or not you ever deploy to Trinity.

/agent-dev:agent-fleet-migrate

Executes that work order non-destructively: sources are never mutated. Each agent is copied or scaffolded into fleet-migrated/, its logic extracted per paradigm, every fix delegated to a named marketplace skill, and every copy verified through a review gate. The run ends with a before/after maturity report plus a gated Trinity deploy offer.

Multi-Session Planning

For large projects that span multiple sessions:

/agent-dev:plan

Creates a persistent plan that tracks overall goals and milestones, current session focus, completed work, and next steps.

See Also

create-agent Plugin - Create new agents
trinity Plugin - Deploy, sync, and loop agents on Trinity
Skills and Playbooks - How skills work in Trinity
Abilities Overview - Full toolkit overview