arsenal
免费Use when the user invokes Arsenal, needs help choosing an approach, or wants an end-to-end task handled with the installed Arsenal skills.
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Create, update or resume a GitHub or Linear issue as durable resolution memory when requested.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Read the specific issue and comments before updating it; outside the duplicate check, do not query unrelated issues. Capture the problem, evidence, attempts, remaining action and verification so the issue can be resumed cold. Use references/issue-template.md when creating one.
Read the project's CLAUDE.md first (AGENTS.md in harnesses that read that
instead). A line naming Linear, such as Issue tracker: Linear, team <name>,
selects Linear. Otherwise use GitHub through the authenticated gh CLI,
unchanged. Label, priority, project, parent and template follow that file
when it names them; never guess one.
Linear goes through the Linear MCP server already connected, whatever its
tool prefix: list_issues, get_issue, save_issue, list_comments,
save_comment. Without those tools, stop: create nothing on GitHub instead,
and give the setup. In Claude Code:
claude mcp add --transport http linear-server https://mcp.linear.app/mcp,
then /mcp to sign in; elsewhere, the client's Linear connector or MCP
setup with that URL.
Before create and from-tasks, search the open issues with the topic's
key words: gh issue list --search "<words>" --state open, or on Linear
list_issues with query and the team, ignoring completed and canceled
ones. Show a close match first, with the offer to add to it (update)
instead of creating a new one. Nothing is created without confirmation.
Confirm before creating or closing an issue. Preserve the Pickup Directive contract. No code changes, commits or agents.
On GitHub, append requested progress as comments instead of overwriting the
body. Label new issues arsenal; keep claude-memory on the ones that
already carry it and match either when listing or resuming.
On Linear, create is save_issue with title, team, the template as
description and the fields the CLAUDE.md names. update keeps one
progress comment per issue: find it with list_comments (it starts with
## Progress), rewrite it with save_comment and its id, and create it
only when none exists. resume reads get_issue and list_comments.
list returns the team's open issues, narrowed by the label or project the
CLAUDE.md names.
from-tasks <brief folder> creates one issue per top-level ## task of
tasks.md, after a single confirmation for the whole batch. Each body uses
the template: Problem from the task and the acceptance criteria it cites,
Pickup Directive with the brief path, base and branch from the brief
frontmatter, the task identifier and its check command. It then writes
[#N](url) ([ID](url) on Linear) into each task heading and the range or
the identifiers into the brief issues field. Existing links are kept,
never duplicated.
close #N appends a Resolution: comment from the evidence given (trace
row, commit, PR) and closes the issue as completed. Ship calls it after a
merge into a branch that is not the default one, where GitHub's Closes #N
does nothing. On Linear, close adds the Resolution: comment, then moves
the issue to the team's completed status with save_issue (state),
unless the CLAUDE.md leaves that to an integration: then the comment only.
After every create, end with one line asking whether to turn the issue
into a brief (« On en fait un brief ? » in the conversation language), with
the command in the harness syntax (/brief:brief #N in Claude Code). Never
start it yourself; Arsenal owns the transition.
Resume reconstructs the current state from the issue, not stale memory. A solved issue does not trigger another diagnosis. List returns concise open items and stops. If the controlled shell has no external networking, report that authorization/capability boundary instead of claiming the tracker action happened or attempting an execution escape.
Return issue context and remaining actions to Arsenal when it called this skill. A request to fix the issue can continue through Arsenal's implementation route; reading or resuming context alone does not authorize code changes. Issue creation and closure retain their confirmation gates.
Before stating an external fact (a version, an API, a price, a date, a
regulation, the behaviour of a tool or library, a person or company), search
first when the runtime offers web search: read the websearch skill and run
one quick search, then cite the source. One search per fact; --deep only on
request. Without web search, mark the claim unverified. Facts visible in the
repository or the request need no search.
Work solo. Ask before any subagent or reviewer, even in auto mode. Explain the independent scope and expected benefit first. No hidden advisor, nested delegation, model retuning, repeated successful checks, or progress spam. Use existing context before asking questions. Stop when the requested result is delivered. User stops and scope changes override pending steps.
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Use when the user invokes Arsenal, needs help choosing an approach, or wants an end-to-end task handled with the installed Arsenal skills.
中文简介正在准备中。当前显示原文说明。
Write a product brief and its task list when the user requests a product specification. Never implement it.
中文简介正在准备中。当前显示原文说明。
Start a session from what was left - trace saves, briefs, proposals, review reports, issues - and ask what to continue. Never resume or implement automatically.
中文简介正在准备中。当前显示原文说明。
Design a concrete technical proposal with evidence and tradeoffs when a decision needs design. No implementation or automatic reviewer.
中文简介正在准备中。当前显示原文说明。
Deep code review driven by a short interview. Read-only reader agents analyze the chosen scope per angle, the lead verifies every finding, and each point is routed to the skill that fixes it. Never edits the code.
中文简介正在准备中。当前显示原文说明。
Implement a clear request or an approved brief/proposal. Work solo, make the smallest sufficient change, verify the changed behavior, and stop. Ask before any delegation.
中文简介正在准备中。当前显示原文说明。