Borrowing it
Nothing to install: this file belongs to ReviewStage/stage-cli. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ReviewStage/stage-cli/main/.agents/skills/linear-issue/SKILL.mdgit clone --depth 1 https://github.com/ReviewStage/stage-cliWrote 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/reviewstage/stage-cli/linear-issue)<a href="https://agentmods.dev/skills/reviewstage/stage-cli/linear-issue"><img src="https://agentmods.dev/badge/skills/reviewstage/stage-cli/linear-issue/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/reviewstage/stage-cli/linear-issue"><img src="https://agentmods.dev/badge/skills/reviewstage/stage-cli/linear-issue.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 174 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 | $0.00047 | $0.01896 |
| Opus 5.5 | $0.00019 | $0.00758 |
| Sonnet 5.5 | $0.00009 | $0.00379 |
| Haiku 4.5 | $0.00005 | $0.00190 |
Grade A, and why
linear-issue 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 1mo 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 — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Creating Linear Issues
Single-pass workflow: gather context, search existing issues, infer fields informed by what's already filed, create issue.
Workflow
1. CONTEXT → Gather signals: args, conversation, directory, git branch
2. SEARCH → list_issues broadly to find duplicates, related issues, and inform inference
3. TEAMS → list_teams to get available teams (informed by search results)
4. INFER → Determine title, description, team, priority, status, labels, project, links, relationships
5. CREATE → create_issue with inferred fields + relationships
6. REPORT → Display created issue summary
Step 1: CONTEXT
Gather all available signals:
- Args: Description provided after
/linear-issue— primary signal - Conversation: If no args, summarize current discussion as issue description
- Directory: Current working directory/package (e.g.
packages/ai/suggests AI-related team) - Git branch: Branch name often encodes feature/bug context
Step 2: SEARCH
Search existing issues before anything else — what's already filed informs every downstream decision including team selection.
- Call
list_issueswith keywords extracted from the context (args, conversation summary, branch name) - Search broadly across teams — no team filter yet, since search results may reveal the correct team
- Collect results into three buckets:
| Bucket | Criteria | Used for |
|---|---|---|
| Duplicates | Same intent and scope as new issue | Stop and warn user |
| Related | Same area, overlapping context | Relationship inference in Step 4 |
| Informative | Same team/area but different scope | Team/priority/status inference in Step 4 |
If a strong duplicate is found (same intent and scope): STOP. Do not proceed to Step 4. Report the existing issue:
Possible duplicate found — did not create.
Existing: TEAM-99 "Add retry logic to extraction agent"
Status: In Progress | Assignee: @charles
URL: https://linear.app/...
Reply if you still want to create a new issue.
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.
- 1mo ago First seen · 185 lines · 47 tokens per session scan A 9b5d92b0f6eb
linear-issue is a skill published in the GitHub repository ReviewStage/stage-cli (274 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 1,896 once invoked, about $0.0002 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.
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