goal-acceptance

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Acceptance-criteria-driven goal completion for autonomous AI agents.

Prevents agents from prematurely declaring "done" by locking immutable acceptance criteria before work begins, tracking validation status with evidence, linking criteria to task progress, respecting dependency ordering, and enforcing completion checks.

Advantages

1. Cross-platform compatibility

One package, four runtimes, 22 install targets:

The core state machine is zero-dependency. The cli mcp server, the dsh Cordis plugin, and the OpenClaw native plugin all call the same shared engine and goal manager — one implementation, four surfaces.

2. One installer for 22 agent platforms

dist/cli.js install --target <name> registers the plugin for 22 clients:

• Native MCP (8): claude, codex, opencode, qwen, reasonix, kilo, workbuddy, devin
• Skill targets (4): trae, pi, omp, dsh
• Agent Plugins (10): copilot, cursor, kiro, openclaw, hermes, vscode, chatgpt-codex, grok, nanoclaw, other

Each adapter writes the client's native config (MCP server entries, skills, plugin dirs, marketplace shims) from one generated portable package (plugin.json / mcp.json / .mcp.json / skills/ / openclaw.plugin.json / openclaw-dist/).

3. MCP server with 18 tools

The CLI exposes 18 tools covering the full goal-acceptance lifecycle:

• Criteria management: set, get, amend
• Task plan management: set task plan, get task plan
• Validation: validate criterion with typed evidence; confirm criterion with independent reviewer evidence
• Progress tracking: update task status
• Completion gate: can complete goal
• Multi-goal management: start goal, create goal, list goals, switch goal, reset goal
• Fast path: quick start goal (start + criteria + optional task plan in one call)
• Run and validate: execute a shell command and validate a criterion in one call

See MCP Tools below for the full list.

Multi-goal isolation

Each goal has its own event file under ${PLUGIN_DATA}/goals/{goalId}.json —multiple projects and windows can share one server without lock conflicts:

• set_acceptance_criteria auto-creates a goal when none is active
• start_goal begins a new independent goal (fresh criteria + task plan)
• switch_goal moves between goals; list_goals shows all with status
• reset_goal deletes a messed-up goal so you can start over
• The active goal survives server restarts (current-goal.txt)

4. Dual-role validation (anti self-grading)

set_acceptance_criteria accepts a role parameter (agent / reviewer / dual). When role=agent, validate_criterion marks passed as selfClaimed=true — can_complete_goal blocks completion until a reviewer formally confirms. This breaks the "self-grading" loop where an agent both does the work and signs off on it.

5. Typed evidence

validate_criterion accepts evidence_type (command / file / url / text). text evidence is flagged lowConfidence=true so reviewers can spot subjective claims at a glance. command evidence (test output, CLI results) is high-confidence.

6. Task decomposition with dependency validation

set_task_plan lets you decompose a goal into atomic tasks, each with a concrete deliverable. The engine validates: unique IDs, unambiguous descriptions, non-empty deliverables, no self-dependencies, no unknown dependencies, and no dependency cycles (including indirect cycles).

7. Event-sourced persistence

All state changes are append-only events. The engine replays events on every read, enabling durable persistence, exact state restoration across restarts, and a full audit trail of every decision.

8. Slim responses by default

MCP tool responses are slim by default (4-field summary). Pass verbose=true for the full summary. This minimizes token overhead during normal operation.

Architecture

src/
├── framework/              # Zero-dependency scaffold (manifest, registry, CLI,
│                           #   wizard, mcp-runtime, hook-runtime, installers)
├── plugin/
│   ├── engine/             # Event-sourced state machine (core)
│   ├── goal-manager.ts     # Multi-goal manager (shared by all paths)
│   ├── tools.ts            # 18 ToolDefs (manifest.tools data source)
│   ├── manifest.ts         # Single source of identity
│   ├── dsh-plugin.ts       # DeepSeek Harness Cordis plugin
│   ├── openclaw-plugin.ts  # OpenClaw native plugin (typebox, in-process)
│   ├── openclaw-session-sync.ts  # Sync active goal to OpenClaw SessionEntry.goal
│   ├── prompt.ts           # dsh system-prompt guidance
│   ├── invariant.ts        # dsh session invariant companion
│   └── targets/            # 22 install adapters
└── assets/                 # SKILL.md + 8 companion skills ({{placeholders}})

build.mjs  →  dist/cli.js (CLI + MCP) + dist/hook.cjs + dist/dsh-plugin.js
              + dist/openclaw-plugin.js → openclaw-dist/
              + plugin.json / mcp.json / .mcp.json / marketplace.json
              / cordis.patch.yml / openclaw.plugin.json / skills/

All identity files are generated from src/plugin/manifest.ts at build time and committed, so the repo is a valid install source for every client.

Quick Start

Install (one command, 22 platforms)

node dist/cli.js install                # interactive wizard
node dist/cli.js install --target claude
node dist/cli.js install --target openclaw
node dist/cli.js list-targets           # show all 22

Plugin marketplaces

This repo doubles as a self-hosted plugin marketplace — the plugin source is ./ (the repo root), so adding the repo makes the plugin discoverable:

# Claude Code (reads .claude-plugin/marketplace.json)
claude plugin marketplace add cckyros/goal-acceptance
# then: /plugin install goal-acceptance@cckyros

# Codex CLI / ChatGPT (reads .agents/plugins/marketplace.json)
codex plugin marketplace add cckyros/goal-acceptance
# then: codex plugin add goal-acceptance@cckyros

# Cursor (reads .cursor-plugin/marketplace.json): add the repo as a plugin
# marketplace in Settings → Plugins

The repo also carries server.json, the descriptor for the official MCP registry (mcp-publisher publish after mcp-publisher login github — namespace io.github.cckyros/goal-acceptance).

MCP server (any MCP client)

{
  "mcpServers": {
    "@cckyros/goal-acceptance": {
      "type": "stdio",
      "command": "node",
      "args": ["/path/to/goal-acceptance/dist/cli.js", "mcp"],
      "env": { "PLUGIN_DATA": "/path/to/persistent/data" }
    }
  }
}

Standalone:

# In-memory (resets on restart)
node dist/cli.js mcp

# Persistent across restarts
PLUGIN_DATA=/path/to/data node dist/cli.js mcp

If PLUGIN_DATA is not set, state is in-memory only (lost on restart).

Typical workflow

1. Set criteria — set_acceptance_criteria with role=reviewer (you verify) or role=agent (agent self-claims, you confirm later)
2. Set task plan — set_task_plan to decompose the goal into atomic tasks with deliverables and dependencies
3. Execute — update_task_status as tasks progress (pending — in_progress — completed)
4. Validate — validate_criterion with evidence_type=command for high-confidence evidence. Default role=agent: passed criteria are self-claimed.
5. Confirm — confirm_criterion (independent reviewer agent only) with fresh evidence_type=command/file/url evidence. Converts self-claimed to formal pass.
6. Check — can_complete_goal to verify all required criteria are formally passed

Orchestrated task loop (worker + reviewer subagents, single-layer review):

1. Dispatch — claim_task marks the next dependency-ready task in_progress and returns it with its linked criteria (the task-level acceptance contract)
2. Review — an independent reviewer subagent calls review_task with per-criterion verdicts. Verdicts are formal: a single validation layer, no self-claim/confirm chain
3. Loop — rejection keeps the task in_progress, blockingCriteria is the rework feedback; fix and review_task again. On full pass the task completes and nextTask is returned, ready to claim
4. Gate — can_complete_goal (or goal-acceptance check) still guards overall goal completion

OpenClaw native plugin

openclaw-dist/ carries the in-process plugin (bundle + minimal package.json with the openclaw.extensions contract) and openclaw.plugin.json declares the 18-tool contracts:

openclaw plugins install @cckyros/goal-acceptance
# or, for a local build:
openclaw plugins install /path/to/goal-acceptance/openclaw-dist
openclaw gateway restart
openclaw plugins list            # goal-acceptance: loaded

The 18 tools are available in OpenClaw sessions. Shape: non-capability is normal for tool plugins — tools are registered via defineToolPlugin.

After every tool that mutates goal state (start_goal, set_acceptance_criteria, validate_criterion, confirm_criterion, amend_acceptance_criteria, update_task_status, set_task_plan, run_and_validate, quick_start_goal, switch_goal, reset_goal), the plugin mirrors the active acceptance goal into OpenClaw's canonical SessionEntry.goal slot. This means OpenClaw's built-in get_goal and update_goal tools see a live snapshot of the acceptance goal. The mirror is write-through: calling update_goal directly updates SessionEntry.goal, and subsequent plugin tools re-sync the slot from the plugin's own event-sourced state.

DeepSeek Harness (Cordis plugin)

dist/dsh-plugin.js is the only variant that can force the agent to continue working when it tries to stop early. It intercepts agent/turn-stopping and steers the agent back with dependency-aware priority ordering.

# cordis.patch.yml (generated)
- insert:
    - id: @cckyros/goal-acceptance
      name: @cckyros/goal-acceptance
      config: {}

The plugin:

• Registers the same 18 model tools as the MCP adapter
• Injects a policy:goal-acceptance system prompt section with task progress and next-actionable ordering
• Intercepts agent/turn-stopping and steers the agent back with dependency-aware priority ordering for pending work and self-claimed criteria awaiting reviewer confirmation

Note: The dsh plugin requires the DeepSeek Harness host packages as peer dependencies (@deepseek-ai/*), injected at runtime by the dsh profile. @deepseek-ai/* imports are devDependencies here for types only.

Core engine (any JS/TS runtime)

The zero-dependency state machine lives in src/plugin/engine/ and is bundled into the CLI. Use it programmatically from this repo or copy the folder into your project:

import { GoalAcceptanceEngine, InMemoryAcceptanceStore } from './src/plugin/engine/index.ts'

const engine = new GoalAcceptanceEngine(new InMemoryAcceptanceStore())

// Lock criteria before work begins
await engine.setCriteria([
  { id: 'api-200', description: 'GET /health returns 200', required: true, method: 'test', taskIds: ['task-1', 'task-2'] },
  { id: 'docs', description: 'README updated', required: false, method: 'manual', dependsOn: ['api-200'] },
])

// Update task progress as work proceeds
await engine.updateTaskStatus({ taskId: 'task-1', status: 'completed' })
await engine.updateTaskStatus({ taskId: 'task-2', status: 'completed' })

// When all linked tasks are done, the criterion is "ready to validate"
const summary = engine.summarize()
console.log(summary.readyToValidate.map(c => c.id)) // ['api-200']

// Record validation with evidence
await engine.validateCriterion({
  criterionId: 'api-200',
  status: 'passed',
  evidence: 'curl /health -> HTTP 200 OK',
})

// Check if goal can complete
const { allowed, reason } = engine.canComplete()
console.log(allowed, reason)
// true, undefined

Headless gate for orchestrators

check and status expose the completion verdict without speaking MCP, so external loop-drivers (ralph-orchestrator hooks, CI gates, shell scripts) can use can_complete_goal as a hard backpressure gate. Both resolve the data directory exactly like the MCP server (PLUGIN_DATA env / pluginData config) — point the orchestrator and the agent's MCP server at the same dir.

goal-acceptance check    # exit 0 when the goal may complete; exit 1 + the
                         # blocking criteria list on stderr otherwise
goal-acceptance status   # JSON summary: goalId, allowed, criteria, counts

ralph-orchestrator

Wire check into ralph's pre.loop.complete hook with on_error: block: the agent works the criteria via the goal-acceptance MCP server inside the loop, and any LOOP_COMPLETE claim the criteria don't back is rejected, so the loop keeps grinding until the goal is genuinely done. A ready-made config lives at examples/ralph/ralph.yml:

hooks:
  enabled: true
  events:
    pre.loop.complete:
      - name: goal-acceptance-gate
        command: ["goal-acceptance", "check"]
        on_error: block

MCP Tools

Skills

The plugin ships 9 skills (built from src/assets/ with placeholder filling):

skills/
├── goal-acceptance/SKILL.md          # Main skill: workflow + companion index
├── goal-planning/                    # Decompose into coverage-complete criteria first
├── set-acceptance-criteria/          # Lock criteria (criterion quality rules)
├── amend-acceptance-criteria/        # Append criteria when requirements expand
├── get-acceptance-criteria/          # Read current criteria and progress
├── update-task-status/               # Track task status linked to criteria
├── validate-criterion/               # Record status + evidence from real execution
├── confirm-criterion/                # Independent reviewer confirmation (fresh evidence)
└── can-complete-goal/                # Completion gate; self-claimed passes block

Criterion Status Lifecycle

pending -> in_progress -> passed | | +-> failed +-> selfClaimed -> confirm_criterion -> formal pass | +-> blocked +-> not_run (non-required criteria only)

Completion Gate

canComplete() returns { allowed: boolean, reason?: string }:

• Allowed: all required criteria are formally passed (not self-claimed), or no criteria are locked.
• Not allowed: any required criterion is pending, in_progress, failed, blocked, or not_run.
• Not allowed (self-claimed): all required criteria are passed but some are selfClaimed=true (set by an agent, not yet reviewer-confirmed). The reason will indicate how many are awaiting reviewer confirmation.

Event Sourcing

The engine is event-sourced. The store holds an append-only list of:

• goal-acceptance/set —locks the criteria list (with role)
• goal-acceptance/task-plan —locks the task decomposition plan
• goal-acceptance/validate —updates one criterion's status (with evidence type, self-claimed flag)
• goal-acceptance/task-update —updates a linked task's status
• goal-acceptance/amend —appends new criteria after the initial lock

On every read, the engine replays events from the store. This enables:

• Durable persistence (file, database, session log)
• Replay-exact state restoration
• Audit trail of all decisions

Custom Store

Implement GoalAcceptanceStore for your persistence backend:

import type { GoalAcceptanceStore, GoalAcceptanceEvent } from './src/plugin/engine/index.ts'

class MyDbStore implements GoalAcceptanceStore {
  get events(): readonly GoalAcceptanceEvent[] {
    // Return all events in append order
  }

  async append(event: GoalAcceptanceEvent): Promise<void> {
    // Persist the event
  }
}

Four-Way Compatibility

The dsh Cordis plugin is the only variant that can force the agent to continue working when it tries to stop early. The MCP, Agent Plugin, and OpenClaw native variants rely on the model voluntarily calling the tools and following skill instructions.

Repository Layout

src/
├── cli-entry.ts            # CLI entry (bundled to dist/cli.js)
├── hook-entry.ts           # Read hook (bundled to dist/hook.cjs)
├── framework/              # Scaffold framework (manifest, registry, CLI,
│                           #   wizard, mcp-runtime, hook-runtime, paths, cache)
├── plugin/
│   ├── manifest.ts         # Identity single source (name, tools, markers, config)
│   ├── engine/             # Event-sourced state machine (zero-dependency)
│   ├── goal-manager.ts     # Multi-goal manager + stores (shared by all paths)
│   ├── tools.ts            # 18 ToolDefs
│   ├── dsh-plugin.ts       # Cordis plugin (service, tools, steer, prompt)
│   ├── openclaw-plugin.ts  # OpenClaw native plugin
│   ├── openclaw-session-sync.ts  # Sync active goal to OpenClaw SessionEntry.goal
│   ├── prompt.ts           # dsh system-prompt guidance
│   ├── invariant.ts        # dsh session invariant
│   └── targets/            # 22 install adapters
└── assets/                 # SKILL.md + 8 companion skills + cover image
tests/                      # node --test suites (engine, mcp, dsh, targets...)
build.mjs                   # esbuild bundles + identity file generation
dist/                       # cli.js + hook.cjs + dsh-plugin.js (committed)
openclaw-dist/              # openclaw-plugin.js + package.json (committed)

Build & Test

pnpm install
npm run verify      # build → typecheck → node --test
node dist/cli.js --help

License

MIT