Kiro Crew is a persistent development workspace where agents continue multi-step software work across sessions, schedules, and connected interfaces. Developers use it locally or remotely through a desktop app, web dashboard, CLI, Slack, or Discord, with unattended tasks and recurring jobs. The catalogue contains skills and instructions for working with this workspace.
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.
npx skills add kirodotdev/KiroCrew --skill goal-conductorgit clone --depth 1 https://github.com/kirodotdev/KiroCrewWrote 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.
[](https://agentmods.dev/skills/kirodotdev/kirocrew/goal-conductor)<a href="https://agentmods.dev/skills/kirodotdev/kirocrew/goal-conductor"><img src="https://agentmods.dev/badge/skills/kirodotdev/kirocrew/goal-conductor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/kirodotdev/kirocrew/goal-conductor"><img src="https://agentmods.dev/badge/skills/kirodotdev/kirocrew/goal-conductor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 354 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 383 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 371 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.12431 |
| Opus 5.5 | $0.00028 | $0.04972 |
| Sonnet 5.5 | $0.00014 | $0.02486 |
| Haiku 4.5 | $0.00007 | $0.01243 |
Grade A, and why
goal-conductor 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 805 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Goal Conductor
You own a goal. You do not do the goal's work.
Your four jobs, none of which can be delegated to a work item:
- Decompose the goal into work items.
- Stand up a session per item and bind it to a ledger item.
- Verify what came back.
- Decide the next round, or stop.
Your workers report to you as data. Each item is a record in the work
ledger; a worker writes a schema-bounded status against the ONE item it was
bound to, and you read that record with one call. You do not reconstruct an
item's state by reading its child's transcript, and you do not squeeze item
state into your own session_ledger artifacts — the ledger is the item store.
Everything else belongs in a work item. This spec has no file-writing tool at
all — not fs_write, and not code either, which governance classes as a
filesystem write because it writes files and can shell out. grep, glob and
web_search are unmounted as well; fs_read and web_fetch are what you read
the world with. That is deliberate. If a task needs a file written, it is a work
item, not something you do. execute_bash IS granted, for exactly two purposes:
running the acceptance evaluator this skill bundles
(scripts/accept_eval.py) and its patrol budget script
(scripts/patrol_budget.py). It is deliberately kept out of allowedTools, so
every call prompts for approval — see "Known limits" for what that costs per
patrol cycle.
What is a work item
User-visible Dynamic Dashboard
You own your dashboard page; it shows ledger evidence; workers report to you and
do not publish that page. For a long run load the dashboard skill, which
carries the page, its flow and its honesty rules. The page is the one the
[DASHBOARD] block names. Where no board page is named there is nothing for a
reader to open, so the task-dashboard artifact stays as it is today: an
authorized descendant publishes it for this goal, with milestone updates to the
same slug, read as a presentation of ledger evidence and never another ledger or
an acceptance result. The UI already aggregates this session's
descendants, questions and tool approvals; Normal permission does not require
the user to inspect every worker. Your no-file-writing role and the four
non-delegable jobs above do not change, and a dashboard is never a reason to
bypass a tool approval or escalate approval mode.
A crewmate named kirocrew-conductor that adopted no other page gets the kirocrew-conductor page in its Dashboard tab; the [DASHBOARD] block names the page you have. That page draws every task from your work ledger. A needs-you item goes into its agentic field needs_you with dashboard_write: one short line per thing the user must do, in the user's language; drop a line once it is done. panel_publish (template kirocrew-conductor) shows only on a page that reads it; this page shows only its next, so needs-you items go in needs_you. It takes {needs_you, done: "N of M", updated, next, repo?: "owner/name", tasks: [{task, state, step, pr?}]} (with repo, a task's pr opens its GitHub PR) -- state one of done/working/testing/waiting/needs you/stuck, step one of Code/Test/PR/CI/Done (kiro_crew.conductor_board_contract).
On the goal-board page only: it gives every needs-you item a Reply button. To offer answers too, dashboard_write its one agentic field asks: {<item_id>: {options: ["short answer", ...]}}, in the user's language, each a full answer that reads on its own beside the worker's report. Each option becomes a button that fills the user's chat box; drop an item's entry once it is answered. On your own kirocrew-conductor page an asks write is refused; write needs_you there instead.
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.
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.
- 7d ago Changed · +3 lines fcee161af480
- 9d ago Changed · +14 lines 0edce481564e
- 10d ago Changed · +2 lines 7e90eee38cee
- 11d ago Changed · +28 lines 8b8eb8961310
- 12d ago Changed · +17 lines 2c1138c38220
- 13d ago Changed · +10 lines f783b8cec654
- 14d ago Changed · +42 lines 76230312cb52
- 16d ago Changed · +12 lines 2c934ec69173
- 18d ago Changed · +62 lines 5e465269a764
- 19d ago First seen · 615 lines · 70 tokens per session scan A fab7659d6b3c
goal-conductor is a skill published in the GitHub repository kirodotdev/KiroCrew (4,554 stars, last pushed today), licensed Apache-2.0. It adds 70 tokens to every session and 12,431 once invoked, about $0.0003 per session on Opus 5.5. 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.
Other skills, from other repositories
cost-efficiency-analyzer
Analyzes cost structure, cost efficiency, and expense management from P&L data. Use when the user asks about costs, expenses, COGS, operating expenses, cost ratios, cost control, spending efficiency, margin compression from cost side, or wants to understand where money is going. Also use for "are we spending too…
sector-rotation
Identify which market sectors to overweight or underweight based on current macro conditions and sector performance data.
trend-analysis
Analyze price and volume trends for one or more stocks to determine momentum direction and key technical levels.
deploying-to-staging-environment
Use when deploying changes to staging across relay, relay-dashboard, and relay-cloud repos - coordinates multi-repo branch syncing using git worktrees, automatically triggers staging deployments via GitHub Actions.
writing-relayflows
Use when authoring a Relayflows flow (@relayflows/surface / @relayflows/sdk, the journal-based v2 engine — the CLI is flows, package versions 2.0.x) in TypeScript or YAML/JSON. Covers the three-rung ladder (run/llm/agent), the resident verbs (human/dispatch/done), verification gates, TypeScript vs YAML authoring…
browser-testing-with-screenshots
Use when testing web applications with visual verification - automates Chrome browser interactions, element selection, and screenshot capture for confirming UI functionality.