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 agentmods add skills/acendas/shipyard/dispatching-operational-tasknpx skills add Acendas/shipyard --skill dispatching-operational-taskgit clone --depth 1 https://github.com/Acendas/shipyardWhat 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 | $0.00015 | $0.04752 |
| Opus 5 | $0.00008 | $0.02376 |
| Sonnet 5 | $0.00003 | $0.00950 |
| Haiku 4.5 | $0.00002 | $0.00475 |
Grade A, and why
dispatching-operational-task 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 2d 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 — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dispatching an Operational Task
Render before asking. Before any AskUserQuestion, render the decision context as assistant chat text. Content that exists only in a Read result, a subagent/Agent return, or the question/option strings does not count as rendered (the UI shows a compact card) — restate it in chat first.
A kind: operational task is one whose deliverable is a successful run of a named command, captured to disk so the orchestrator and /ship-review can verify it actually happened. Examples: "Run the full E2E suite and fix findings until green," "Run the security audit and fix HIGH issues," "Bring the linter to zero errors."
Operational tasks have no Red step, no acceptance probe (the command itself is the gate), and no atomic feature commit (fixes commit as they go). Mis-routing this through dispatching-task-loop is the silent-pass bug — the feature builder has no work to do (no Red, tests already exist), exits clean on an empty tree, and the "Before Exiting" gate trivially passes. Route here.
Goal-mode default
This skill is /goal-shaped at the operational-task level: "run until the verify command exits 0." The Phase 1 (run+capture) → Phase 2 (fix-findings) → Phase 1 cycle is the /goal loop. It runs max_iterations (default 3 from config) times before returning STATUS: BLOCKED — there is no flag, no opt-in, no user prompt mid-loop. The cap is the only escape; otherwise the subagent stays inside the loop until the verify command exits 0. (This loop runs synchronously via Monitor; for the broader /goal-loop pacing discipline shared with the ScheduleWakeup-driven wave/sprint verifiers, see references/schedule-wakeup-discipline.md.)
The orchestrator does not surface mid-loop to the user. The subagent absorbs every fix attempt, every re-run, every patch-task filing. Only the final structured return — STATUS: COMPLETE with verify_output: populated and the last capture's exit:0, or STATUS: BLOCKED with the failing-tail summary — reaches the orchestrator. The caller summarizes that contract; it does not forward subagent preamble, epilogue, or incidental commentary.
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.
- 2d ago First seen · 230 lines · 15 tokens per session scan A 0a62868c512f
dispatching-operational-task is a skill published in the GitHub repository Acendas/shipyard (2 stars, last pushed 20d ago), licensed MIT. It adds 15 tokens to every session and 4,752 once invoked, about $0.0001 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 2026-08-31.
Other skills, from other repositories
engenharia-de-requisitos
Use when doing requirements engineering, business analysis, or the software-engineering stage of discovering / specifying / validating / managing requirements — the stage BEFORE code (what to build) and AFTER (was the right thing built?), for new projects and for evolutions of existing ones. Triggers (EN)…
engenharia-de-requisitos
Use when doing requirements engineering, business analysis, or the software-engineering stage of discovering / specifying / validating / managing requirements — the stage BEFORE code (what to build) and AFTER (was the right thing built?), for new projects and for evolutions of existing ones. Triggers (EN)…
write-epic
Produces a complete epic definition following Atlassian agile guidance. An epic captures a large initiative that is too big for a single sprint and must be decomposed into user stories.
write-user-story
Produces a complete, ready-to-groom user story following the standard Atlassian/agile format. It applies the INVEST criteria and the 3 Cs framework (Card, Conversation, Confirmation) to ensure each story is well-scoped, valuable, and testable — not just syntactically correct.
backlog-grooming
Review Agiflow Planning tasks for readiness, prioritize approved work, group related tasks into work units, and promote ready tasks to Todo. Use when grooming a backlog, organizing planned tasks, creating work units, or deciding what should be executed next.
project-plan
Turn a product goal or feature request into a clear Agiflow project plan with small, testable tasks in Planning status. Use when starting a project, decomposing a feature, clarifying requirements, or converting an idea into an actionable backlog.