Goal logo

Goal

Community
coco-research
goal

Persistent project goal that survives across sessions and tools, with continuous-execution loop semantics. Use when someone asks to "set a goal", "what is my goal", "goal status", "keep working on X until done", "resume the goal", or wants work to continue across sessions until an objective is achieved. File-backed (.goal.md at project root); shared by every Coco-installed tool working in that repository.

Overview

Publishercoco-research
Repositorycoco
Skill namegoal
Stars
550
Forks
12
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by coco-research on GitHub. Read the source before you install it.

Installation

Install the Goal 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.
    https://github.com/coco-research/coco/tree/main/skills/goal
  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/coco-research/coco.git /tmp/coco
mkdir -p .claude/skills
cp -r /tmp/coco/skills/goal .claude/skills/goal
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Goal 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 Goal 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 Goal 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.

Goal — persistent project objective

A goal is a single objective the agent keeps pursuing across turns and sessions until it is marked done. Inspired by Prime Agent's thread goal: state lives outside any one conversation, so any tool with this skill installed (Claude Code, Cursor, Codex, ...) picks up where another left off.

State file

One file per project: .goal.md in the repository root. Human-readable and human-editable on purpose — pause, resume, edit, and clear are controlled by the user editing the file directly.

markdown
---
objective: Ship release notes for v2.3
status: active        # active | paused | done
created: 2026-08-22
---

## Progress
- 2026-08-22 14:02 — drafted changelog from git log

Optional sections the loop reads if present: ## Queue (ordered work items), ## Standing constraints (owner-set rules that bind every session), ## Decisions (recorded owner calls — binding, never re-litigated), ## Done criteria.

API

  • get — read .goal.md. No file means no goal is set. Report the objective, status, and latest progress entries when asked about goal status.
  • create(objective) — write .goal.md with status: active and today's date. If an active goal already exists, do NOT silently replace it; show it and ask whether to complete, pause, or replace. Only create a goal when the user explicitly asks for a persistent goal; do not infer goals from ordinary tasks.
  • update(note) — append one dated line to ## Progress after each meaningful work session toward the goal. Keep notes short and factual.
  • complete() — set status: done. Only when the objective has actually been achieved and no required work remains — not because the session is ending or momentum ran out.

Session behavior

At the start of a session in a repo containing .goal.md:

  • status: active — surface the objective to the user, then ENTER THE WORK LOOP below before starting unrelated work.
  • status: paused — mention it exists; resume only if the user asks.
  • status: done — leave it as history; offer to archive or replace.

Work loop (continuous execution)

An active goal with remaining actionable items means you run a LOOP, not a single pass. One iteration:

  1. Resume — read .goal.md plus the newest handoff document it references (typically under docs/plans/). Verify recorded receipts against reality (HEAD sha, merged PRs, live state) before trusting them.
  2. Pick the highest-priority item that is actionable right now — from the Queue, the referenced workorder, or the handoff's "exact next action".
  3. Journal before acting — append TODO <task> to ## Progress. If the session dies here, a successor knows precisely what was attempted.
  4. Execute — do the work. Run the real gates. Commit/PR per whatever authority the goal grants (e.g., self-review-and-merge if so recorded).
  5. Journal after — append DONE <task> — <receipt> immediately. Receipt = commit sha, PR number, test counts, or posted artifact. No receipt, not done.
  6. Repeat from step 2 while an actionable item remains and no STOP condition applies.

Never end a turn with actionable items outstanding unless a STOP condition fired. "Momentum ran out" is not a stop condition.

Failure resilience

  • Transient LLM/API/tool failures — timeouts, 429/5xx, dropped connections — are NEVER stop conditions. Retry with backoff (≈30s → 60s → 120s, cap ~5 attempts). If one dependency stays down, journal BLOCKED <item> — <reason>, switch to the next non-dependent actionable item, and circle back.
  • Crash/interrupt safety: because TODO precedes work and DONE follows it, an interrupted session loses nothing. On resume, a task with TODO and no DONE is simply not started yet — verify no half-committed debris, then restart it.
  • Tool/environment failure ≠ task failure. A failing gate gets diagnosed; a failing external service gets routed around; neither ends the loop.
  • Flaky tests fail-then-pass-isolated are recorded as known-flaky, not treated as regressions — but always rerun isolated before concluding that.

Stop conditions (the ONLY reasons to end the loop)

  1. Done — goal achieved; call complete().
  2. Blocked on owner — every remaining item needs an answer only the owner can give. Post the questions (one line each), mark items BLOCKED/DEFERRED, update .goal.md, stop with a clear summary of what you need.
  3. Context limit approaching — write the handoff document (see Handoff), append the final Progress line, stop cleanly.
  4. Repeated hard failure — ≥3 consecutive unrecoverable failures across DIFFERENT items (not retries of one) → write an incident note into Progress and the handoff, stop, report to owner.

Everything else — API flakiness, slow builds, flaky tests, waiting on a local service — is worked through or routed around.

Handoff (graceful exit)

If the repo keeps committed plan/handoff documents (e.g., docs/plans/), the graceful exit is: write/update the handoff file containing exact HEAD sha, PRs landed this session, current queue position, receipts, known gotchas, and the exact next action — then append the final Progress line to .goal.md, then stop. Ending a session without those two writes is a defect: the successor must be able to resume from .goal.md + the latest handoff alone.

Rules

  • One active goal per repository. The file is the source of truth — never keep goal state only in conversation memory.
  • Never delete or rewrite past progress lines; append.
  • Completion must reflect reality. An agent that marks a half-finished goal done defeats the entire mechanism.
  • Standing constraints and recorded decisions inside .goal.md bind every session and outrank this skill's defaults.
  • Journal honestly: a TODO line without a matching DONE line is expected and safe; a DONE line without receipts is a lie.

Harness note (out of skill scope)

This skill makes the AGENT persistent within a session and recoverable across sessions. Fully automatic relaunch after a dead session requires harness-level scheduling (cron/gateway/watchdog) outside any skill's control. If the owner wants unattended overnight loops, pair this skill with a scheduler that re-invokes the agent with "resume the goal".

Frequently asked questions

What does the Goal AI skill do?

Persistent project goal that survives across sessions and tools, with continuous-execution loop semantics. Use when someone asks to "set a goal", "what is my goal", "goal status", "keep working on X until done", "resume the goal", or wants work to continue across sessions until an objective is achieved. File-backed (.goal.md at project root); shared by every Coco-installed tool working in that repository.

Why use Goal on TypingMind?

Because you install it once and use it with any model. Goal 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 Goal in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/coco-research/coco/tree/main/skills/goal. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Goal?

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 Goal?

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

Is the Goal AI skill free?

It is published on GitHub by coco-research. Check the repository for licensing terms. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇