team
Staged pipeline of coordinated agents: plan → spec → execute → verify → fix, on a shared task list.
Skill by siddicky
Chalk Labs
Need help deploying team?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/siddicky-team
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: data, productivity
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/team
What's inside
- Skill name
team- Description
- Staged pipeline of coordinated agents: plan → spec → execute → verify → fix, on a shared task list.
- License
- MIT
- Instructions
- 64 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# team
Run a coordinated multi-agent pipeline on a shared task list, driving the
dependency-aware execute/verify fan-out from the code interpreter (the `eval`
tool) so the schedule and per-task state stay in JS rather than your context.
1. PLAN — `architect` + `planner` produce the design and the milestone plan;
`critic` validates it.
2. SPEC — turn each milestone into a precise, self-contained task with a
pass-gate and an explicit list of task ids it depends on. Record them with
`write_todos`; this is the authoritative ledger.
3. EXECUTE & VERIFY — in `eval`, walk the dependency graph in waves: each wave is
the set of tasks whose dependencies are all done. Dispatch a wave with
`task()` to the right execution agent (`executor`, `debugger`,
`test-engineer`, `designer`), then dispatch `verifier` on each result against
its gate. Carry only `{ id, ok }` forward to schedule the next wave.
4. FIX — route any failed task back to execution and re-verify it in the next
wave. Close the loop with `code-reviewer` (and `security-reviewer` for
sensitive changes).
Use a `responseSchema` on every `task()` so results are validated objects, and
return only the wave summary. Mutating tools are unavailable inside `eval`, so
all writes happen through the dispatched agents:
```js
const tasks = [ /* { id, summary, agent, gate, deps: [] } from the spec */ ];
const done = new Set();
const summary = [];
const ready = () => tasks.filter((t) => !done.has(t.id) && t.deps.every((d) => done.has(d)));
let wave;
while ((wave = ready()).length > 0) {
const built = await Promise.all(wave.map((t) => task({
description: t.summary,
subagentType: t.agent,
responseSchema: {
type: 'object',
properties: { id: { type: 'string' }, changed: { type: 'array', items: { type: 'string' } } },
required: ['id'],
},
})));
const checked = await Promise.all(wave.map((t) => task({
description: 'Verify task ' + t.id + ' against its gate: ' + t.gate,
subagentType: 'verifier',
responseSchema: {
type: 'object',
properties: { id: { type: 'string' }, ok: { type: 'boolean' }, evidence: { type: 'string' } },
required: ['id', 'ok'],
},
})));
for (const c of checked) {
if (c.ok) done.add(c.id);
summary.push({ id: c.id, ok: c.ok });
}
// Stop scheduling if a wave made no progress (a failing/blocked task).
if (!checked.some((c) => c.ok)) break;
}
summary;
```
Keep the task list authoritative: every unit of work is a tracked task with a
clear owner lane, declared dependencies, and an explicit gate.From siddicky/oh-my-dcode, MIT.
More from siddicky/oh-my-dcode
- 0.471score
ultragoal
siddicky
Durable multi-goal execution: decompose a ratified plan into ordered goals and drive each to an all-pass checkpoint via rubric self-evaluation.
SkillCFreshness: CClaude Code +9 - 0.471score
deep-interview
siddicky
Socratic requirements gate: interview the user in rounds, stress-test from multiple angles, and crystallize a spec before any planning.
SkillCFreshness: CClaude Code +9 - 0.469score
ultrawork
siddicky
Maximum parallelism: decompose the goal into independent units and fan them out across agents at once.
SkillCFreshness: CClaude Code +9 - 0.469score
autopilot
siddicky
Full autonomous execution from idea to verified working code: expand → plan → build → QA → review.
SkillCFreshness: CClaude Code +9 - 0.469score
ralplan
siddicky
Consensus planning gate: produce a plan, stress-test it from multiple perspectives, and converge before building.
SkillCFreshness: CClaude Code +9 - 0.464score
ralph
siddicky
Persistent verify/fix loop: keep iterating on a single goal until a reviewer confirms it is done.
SkillCFreshness: CClaude Code +9 - 0.464score
deepship
siddicky
Full idea-to-shipped pipeline: deep-interview → ralplan → ultragoal → team, run as four gated phases.
SkillCFreshness: CClaude Code +9
Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Jun 22, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/siddicky/oh-my-dcode
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from siddicky
- 0.471score
ultragoal
siddicky
Durable multi-goal execution: decompose a ratified plan into ordered goals and drive each to an all-pass checkpoint via rubric self-evaluation.
SkillCFreshness: CClaude Code +9 - 0.471score
deep-interview
siddicky
Socratic requirements gate: interview the user in rounds, stress-test from multiple angles, and crystallize a spec before any planning.
SkillCFreshness: CClaude Code +9 - 0.469score
ultrawork
siddicky
Maximum parallelism: decompose the goal into independent units and fan them out across agents at once.
SkillCFreshness: CClaude Code +9 - 0.469score
autopilot
siddicky
Full autonomous execution from idea to verified working code: expand → plan → build → QA → review.
SkillCFreshness: CClaude Code +9 - 0.469score
ralplan
siddicky
Consensus planning gate: produce a plan, stress-test it from multiple perspectives, and converge before building.
SkillCFreshness: CClaude Code +9 - 0.464score
ralph
siddicky
Persistent verify/fix loop: keep iterating on a single goal until a reviewer confirms it is done.
SkillCFreshness: CClaude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get team running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
team skill. Agent Mart. https://agentmart.dev/skills/siddicky-team (last updated 2026-10-24)