Orch logo

Orch

Organization
vanillagreencom
orch

PRIMARY AGENT ONLY. Load to orchestrate a Linear or GitHub work item from preparation through merge.

Overview

Publishervanillagreencom
Repositorykendex
Skill nameorch
Stars
80
Forks
31
Bundled files
170
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 170 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by vanillagreencom on GitHub. Read the source before you install it.

Installation

Install the Orch AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/vanillagreencom/kendex.git /tmp/kendex
mkdir -p .claude/skills
cp -r /tmp/kendex/skills/orch .claude/skills/orch
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Orch in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Orch on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Orch is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Orchestration

Load github and worktree before anything else; a Linear work item also needs linear. The dev and reviewer skills call orch scripts.

MODE SWITCH: you are the orchestrator. Delegate every implementation, review, and QA task to a specialist sub-agent. Never edit code unless the user explicitly asks.

The Cycle

Get the issue → dev implements → review → dev fixes blockers → re-review → push PR → review gate → shepherd to merge.

  • Bounded loops. A fix round addresses blockers only; re-review narrows to the fix diff and the domains it touched; two consecutive rounds with no new blocker end the review.
  • No edge-case churn. A finding that cannot affect real usage is declined with a one-line reason, not fixed, not filed.
  • Review must converge, by references/finding-disposition.md:
    • Every finding runs its § Decision flow, Step 0 first, and ends as one of the reply forms that section sets out.
    • A defect class recurring across rounds → its § Recurrence, never patched per comment, for a rule restated in prose or a table as much as for code.
    • A defect in code the issue's Done-when does not need, or a PR whose reviewer or orchestrator chooses a cut from its size report → a cut round. A round whose only findings are scope or wording asks ends the review: reply, resolve, push nothing, merge through the gate. --admin requires the explicit consumer-only answer in submit-pr.md § 6.2.
  • Ask the user only about product or experience. Scope expansion beyond the issue and revisiting a recorded decision always ask, whatever ORCH_DECISION_MODE says. Merge asks unless ORCH_MERGE_AUTONOMY=auto, which merges without asking only when every merge gate is green. In a lane every ask gate is lane-mail, never the harness question tool: references/skill-rules.md § Coordination.
  • Post-PR autonomy. After a PR exists, ORCH_DECISION_MODE=auto-recommended takes and logs the continuing option while a bounded wait, retry, or triage round remains. ask presents the listed choice. workflow-state head-budget take owns automatic retry spending, starting the count over on a changed head for review-wait only. At a cap, workflow-state post-pr-stop record atomically persists the named stop and renders its matching Markdown comment; the workflow posts that file to the PR and returns the stored stop. A nested caller uses record-if-empty so a precise upstream stop wins. Every continuing action clears the stop with workflow-state update. Initialize the resolved state key before these transitions. ORCH_MERGE_AUTONOMY controls merge consent only.
  • The overseer reads results. It accepts a lane's green suite, validation command, and CI without reproducing them. It gives no separate grant to prepare, commit, push, or merge, and uses no shared validation slot. A green lane with existing user merge authorization arms auto-merge itself without a grant, then owns its merge wait to a terminal verdict as workflows/merge-pr.md requires. It accepts a dev agent's test-only validation-ceiling report and does not extend validation. The overseer never sends model or account instructions to a lane. The lane's model is fixed at launch, and the lane launches no lanes.
  • Acceptance is artifact-based. A round closes on a validated on-disk artifact plus git/tracker state, never on a return message.

Commands

Route <command> [args] to its workflow and follow Workflow Execution.

CommandArgumentsWorkflowPurpose
start[ISSUE_ID] | github OWNER/REPO#Nworkflows/start.md / workflows/start-worktree.mdPrepare one work item; from a worktree, run the full session
start newlinear|github ...workflows/start-new.mdCreate one issue, then start it
handofflinear|github ...workflows/handoff.mdLaunch independent sessions
plan-issuesPLAN_PATH linear|githubworkflows/plan-issues.mdConvert plan items into issues
dev-start[ISSUE_ID]workflows/dev-start.mdDelegate implementation
dev-fix[ISSUE_ID]workflows/dev-fix.mdDelegate fix items
ci-fixPR_NUMBER | queueworkflows/ci-fix.mdAnalyze and fix CI failures
review[all] | [last N] | [HASH]workflows/review.mdOn-demand review of local changes
review-codebase[PATH]workflows/review-codebase.mdWhole-codebase fanout, findings only
review-pr[PR_NUMBER]workflows/review-pr.mdReview cycle with fixes and QA
review-pr-commentsPR_NUMBER | BRANCHworkflows/review-pr-comments.mdTriage PR review comments
submit-pr[PR_NUMBER]workflows/submit-pr.mdPush, create PR, gates, merge
merge-prPR_NUMBER | allworkflows/merge-pr.mdVerify conditions and merge
post-summary[ISSUE_ID]workflows/post-summary.mdPost summary and handoff comments
overseenoneworkflows/oversee.mdFleet mode: one session per unblocked item, shepherd every PR to merge

start routing. github OWNER/REPO#NTRACKER=github, ISSUE_ID=issue-N, keep OWNER/REPO for the API; otherwise Linear unless the id starts with issue-. A cwd whose git common dir differs from .git is a worktree → workflows/start-worktree.md; otherwise workflows/start.md.

Scripts

bash
.agents/skills/orch/scripts/<script> [args]
ScriptIntent
workflow-statePersistent state read/write/append. See below
git-contextGit-derived values (branch, head, issue id, roots, timestamps)
pr-view-jsonPR view JSON; status=no_pr exits 0 and routes to PR creation, not an error
resolve-base-branchPrint a worktree's base branch; exits 1 rather than guess
sync-baseResolve, fetch, and fast-forward the checkout that owns the base branch; prints the branch name
container-closeSerialize a Linear container close across linked checkouts; prints closed or deferred, with closed diagnostics on stderr
base-freshnessGate the review cycle on a current base; unverifiable = stale
review-artifact-checkValidate a reviewer's JSON artifact, the sole reviewer completion condition
dev-return-writeWrite a dev agent's round-scoped completion artifact; never hand-author the JSON
worktree-pushPush an issue worktree via worktree push, reconciling rebased SHAs in workflow state (.rebase_map, fixed_items, pr_comment_review.fixes) in the same call; --check-live-round answers whether a fix round is in flight and pushes nothing
dev-round-writePersist a fix round's delegated item set at stamp time; --cut records the round that cuts an oversized branch
dev-artifact-checkValidate a dev round's completion artifact by round id
branch-size-checkReport added production, test and render-mirror lines against the issue's optional **Expected delta**. Size never refuses; malformed allowance text exits 3. --help
approval-waitPoll the reviewer gate; --resolve-mode prints the effective gate mode
ci-waitBlock until CI completes on a PR
queue-waitBlocking merge-queue / auto-merge waiter and verdict producer
orch-envEffective value of a kendex [env] setting (process env > .env.local > .kendex/settings.toml > kendex.settings.toml > default)
spawn-adapterResolve Codex spawn parameters (spawn) and the runtime thread budget (slots)
open-terminalTerminal handoff; model, effort, and permission flags via --launch-flags
lanesEnumerate harness auth lanes; pick prints the launch env prefix for the least-loaded qualifying lane, exit 3 when none qualifies; context reports each live lane's context use; state <item> prints one lane's state from the pane, by the same judge oversee-watch and open-terminal --wake ask
lane-hostResolve or call the configured host provider; protocol: schemas/lane-host.md. Static SSH reference: lane-host-ssh --help
lane-mailThe lane-to-overseer mailbox. A lane runs ask, notice, wait and inbox; the overseer runs send, drain and pending, adding --root and --host for a lane on another host
reconcile-work-itemsRead-only tracker sweep (parked containers, items stale past RECONCILE_STALE_HOURS, Done items with unchecked boxes). Exit 1 on findings
oversee-watchBlock until the fleet needs the overseer, then print one wake carrying every event the pass found
oversee-succeedReplace an overseer past its context mark, or on an account at or below ORCH_OVERSEER_HEADROOM_PCT headroom, with a successor overseer window at the same index; window-below-mark and context-below-mark exit 0, no-lane-qualifies refuses and at mark=account names the account and its reset

Every script takes --help bar pr-view-json and resolve-base-branch, whose only argument is a path. Waiter and gate semantics, including the 3 exit on hard auth failure and reading the effective gate mode (approval, review, off) only through approval-wait --resolve-mode: references/gates.md. Artifact checks: references/artifact-checks.md. Schemas: schemas/workflow-state.md (state file), schemas/dev-return.md (dev completion artifact), schemas/dev-round.md (fix-round item set), ../reviewer/schemas/review-finding.md (review/QA findings).

Multi-PR watching. Never hand-roll a monitor. When .agents/skills/review-gate/scripts/pr-watch.sh exists, run it (oversee: through oversee-watch); otherwise per-PR approval-wait/queue-wait.

workflow-state. Run it with no arguments for the action reference. State keys are normalized issue IDs: issue-N for GitHub, PROJ-123 for Linear.

A queued merge is waited out in the lane: merge-pr.md § 5 step 1 uses Waiter launch and routes the recorded verdict (queue-wait --help § Verdicts). The lane stays active until it can finish the post-merge work.

Configuration

Non-secret settings go in committed kendex.settings.toml under [env]; .env.local holds secrets and personal overrides. Keys: README.md § Settings; review-gate keys in references/gates.md; lane keys in lanes --help and open-terminal --help. System dependencies: jq; bash 3.2; flock and setsid (util-linux).


Runtime Notes

If you are running in Codex: approval required by policy, but AskForApproval is set to Never flags the command's SHAPE. Never retry it, never wait for approval; rewrite it per references/codex-runtime.md. Run long waiters through Waiter launch; CI waiting uses .agents/skills/orch/scripts/ci-wait. Spawn generated agents through scripts/spawn-adapter with fork_context: false, then send_input a DELEGATION:-prefixed <delegation_format>.

If you are running in OpenCode: store the task_id returned by functions.task in workflow state (child_sessions[agent].agent_id, review_agent_ids[reviewer-name]) and re-delegate with functions.task(task_id=<stored_id>). Spawn fresh only when no ID is stored, one resume attempt failed, or the task is confirmed dead.

If you are running in Pi with pi-agents-tmux: delegation is one subagent call whose task argument is the filled <delegation_format> alone. Never prepend role text. Store the returned taskId in workflow state. references/pi-runtime.md.


Skill Rules

Delegation, agent lifecycle, round closure, and coordination: references/skill-rules.md.

Workflow Execution

  • Sequential sections. Mark in-progress, execute every sub-section, mark completed, proceed. Never create tasks for sub-sections, never complete a parent before its children, never skip a step on a predicted outcome.
  • Skip-if. Evaluate "Skip if [condition]" literally; when true, append "(SKIPPED)", mark completed.
  • Nested workflows. Invoke -marked workflows through the harness mechanism, never inlined. Record the return point (→ § X) first.
  • Worktree scope. Inside a worktree, never act on another worktree or branch, never commit or stash in the main checkout, and never run a kendex command that writes the project scope (refresh, apply). Every concurrent session shares that checkout, and those prune it. If the resolved ISSUE_ID differs from the current branch, stop and ask: reuse, abort, or switch.
  • Unsent input is not an instruction. Text already sitting in the composer when a session reaches its prompt belongs to the harness, not to the user: clear it, act on nothing it says.
Harness-Safe Shell

Run exactly one simple command per tool call with explicit arguments. Rejected shapes and substitutes: references/codex-runtime.md. Normalize delegated command lists the same way before they enter a prompt: an env-assignment prefix becomes a precondition check plus the bare command. A finding's location, description, or cause never crosses argv: write it to a file with the harness file-write tool and bind the path (--items-file, append-file, jq --slurpfile).

Tracker Resolution

An ISSUE_ID starting with issue- is GitHub (TRACKER=github, issue number ${ISSUE_ID#issue-}, repo from caller context else gh repo view --json nameWithOwner); anything else is Linear. A caller-supplied tracker wins; resolve once per workflow into TRACKER and ISSUE_REF (#N for GitHub, the Linear identifier otherwise), the only form a Closes line renders. Run Linear only / GitHub only steps only for that tracker; never run linear.sh against a GitHub item.

State Management

Durable data lives in workflow state through the workflow-state CLI only (set-git-head/set-now, never inline substitution). Location: <state-dir>/workflow-state-[ID].json, where <state-dir> is the --state-dir flag, then $ORCH_STATE_DIR, then tmp/.

For workflow state, use the preceding location rule; other temporary session state, including handoffs, lane status, and reviews, defaults to the repository's tmp/, which kendex's managed ignore block covers in every consumer, while docs/ holds tracked repository content and never receives a kendex ignore rule.

After compaction, resume from the step after the last completed one: read workflow state, re-send delegations by stored ID, respawn only an agent silent through one idle cycle. Never repeat completed actions.

Review Pipeline

Finding schema. ../reviewer/schemas/review-finding.md, enforced by review-artifact-check. Routing reads verdict (action_required when blockers exist, else pass) and each suggestion's category ∈ {fix, issue}.

Disposition. Classify each suggestion per references/finding-disposition.md: apply in-PR, file as a tracked issue, or decline with one line. The filing bar lives there.

Issue audit pipeline. Collect every follow-up that clears the filing bar (category=issue suggestions, escalated blockers, dev "deliberately left out" lists, gaps noticed) into audit input (schema in project-management/schemas/), with dependency fields populated when order is known. Apply skill-rules.md § Coordination before issue creation or the TPM audit.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

and 110 more files.

Frequently asked questions

What does the Orch AI skill do?

PRIMARY AGENT ONLY. Load to orchestrate a Linear or GitHub work item from preparation through merge.

Why use Orch on TypingMind?

Because you install it once and use it with any model. Orch is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Orch in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vanillagreencom/kendex/tree/main/skills/orch. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Orch?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Orch?

As many as you like. As long as a model supports skills, you can use Orch with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Orch AI skill free?

Yes. It is published on GitHub by vanillagreencom under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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