teamwork-goal

teamwork-goal is a skill for Claude Code, Codex from JinPLu/Teamwork. It costs 41 tokens per session (600 once invoked), scanned A, original, MIT.

A persistence method for continuing a task until a clearly observable result is reached. It records the objective, constraints, attempts, and stopping conditions.

In plain words
What is it for?
Use it for tasks that must stay active until tests pass, a monitored condition changes, or another stated completion signal appears.
Why use it?
It reduces the chance of stopping after a partial fix or repeating the same failed action without new evidence.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/jinplu/teamwork/teamwork-goal
Any agent
npx skills add JinPLu/Teamwork --skill teamwork-goal
Clone the repo
git clone --depth 1 https://github.com/JinPLu/Teamwork

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for teamwork-goal

README.md
[![agentmods](https://agentmods.dev/badge/skills/jinplu/teamwork/teamwork-goal.svg)](https://agentmods.dev/skills/jinplu/teamwork/teamwork-goal)
Your own site
<a href="https://agentmods.dev/skills/jinplu/teamwork/teamwork-goal"><img src="https://agentmods.dev/badge/skills/jinplu/teamwork/teamwork-goal.svg" alt="Measured on agentmods" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 600 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00041 $0.00600
Opus 5 $0.00020 $0.00300
Sonnet 5 $0.00008 $0.00120
Haiku 4.5 $0.00004 $0.00060

Measured 5d ago against content hash 01671d5d7a22, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

teamwork-goal scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/teamwork-goal/SKILL.md · 58 lines

How it starts

The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Teamwork Goal

Goal adds persistence to the underlying task; it does not add a second workflow.

Method

  1. State the concrete objective, success signal, applicable scope, and any user budget. A success signal is the directly observable result that shows the requested outcome is achieved. Example: the authorized command or user-stated completion condition is observed on the real path.
  2. Perform the next useful action and observe the result.
  3. Continue until the success signal is directly observed, the user interrupts, or a genuine external blocker prevents further progress.
  4. Change approach when evidence invalidates the current one. Do not repeat a failed action without a new reason.
  5. Report success with the observed evidence, or report the exact blocker and what would unblock it.

Carry compact Invariants through every retry: the original objective, protected constraints, and stop or budget state. After each attempt, keep an Attempt Record with the previous result, the new reason to continue or stop, and the current stop or budget state. These records live in the working context and, when a checkpoint fires, in the report; they are not a workflow database.

Tests support the goal but do not replace the real success signal when that signal is available.

Persistence

When a listed checkpoint fires, write in the same response cycle. If separate stable identities each cross a checkpoint, write each to its own path.

Cross-chat memory lives in one Markdown document from references/report.md at docs/teamwork/reports/<slug>.md. Same identity means the same continuing objective; reuse that path and name the document you read. A different subject gets a new path.

Experiment checkpoints write from references/experiment-record.md at docs/teamwork/experiments/<slug>.md. Same identity means the same falsifiable claim; reuse that path and name the document you read. A different claim gets a new path. Probe declarations need only a claim draft, kill criterion, and budget. The full declaration is for main-table or appendix-hygiene eligibility, not a run gate. Slot criteria are in ../teamwork-collaborate/references/experiment.md. Post-run HARKing is the diff between the frozen declared claim and a post-hoc claim; Reviewer or Challenger is the right role for that adjudication, and it is not a mandatory ceremony.

Read the full file on GitHub · 58 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 58 lines · 41 tokens per session scan A 01671d5d7a22

Subscribe to this mod's changes

teamwork-goal is a skill published in the GitHub repository JinPLu/Teamwork (11 stars, last pushed 9d ago), licensed MIT. It adds 41 tokens to every session and 600 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

data-charts-tako

Search and visualize the world's data - get charts, insights, and embeddable knowledge cards for finance, economics, demographics, sports, and more.

gooseworks-ai/goose-skills · 35 tokens

apollo-lead-finder

Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact). Creates Apollo lists. Deduplicates against existing contacts by LinkedIn URL.

gooseworks-ai/goose-skills · 51 tokens

monorepo-management

Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.

wshobson/agents · 54 tokens

browse-and-evaluate

Use when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing. Always use --fields to limit output size and --dry-run before committing to an install.

MoizIbnYousaf/Ai-Agent-Skills · 43 tokens

render-airdrop-carousel

Assemble a viral iOS "AirDrop" notification-carousel video ad (≈6–8s, 9:16) from a brand line plus 6–16 real product photos — a native AirDrop share-sheet card ("Brand would like to share a · Decline / Accept") springs up and its preview window CYCLES through the products, landing on a range/lineup payoff with an…

gooseworks-ai/goose-skills · 207 tokens

render-3d-product-showcase

Assemble a premium 3D product-showcase ad from a config — four beat clips (an orbiting hero rotation, a macro push-in, a physics reveal, a typographic close) normalized to the brand-color canvas, hard-concatenated in order, closed on a deterministic Playwright brand end card, and mixed under one instrumental bed at…

gooseworks-ai/goose-skills · 159 tokens