linear

A connection between a coding agent and Linear, a tool for tracking software issues and tasks. It lets the agent use Linear’s API to find, create, update, and search issues, including issues assigned to you.

In plain words
What is it for?
Use it to list or search Linear issues, create and update tasks, and find work assigned to you or a particular team.
Why use it?
It removes the need to switch between the coding agent and Linear or manually identify your account and team. It also makes requests such as “show my issues” use the correct person.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/suyoumo/clawprobench/linear
Any agent
npx skills add suyoumo/ClawProBench --skill linear
Clone the repo
git clone --depth 1 https://github.com/suyoumo/ClawProBench

Made for: Claude Code, Codex.

Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,755 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00045 $0.01755
Opus 5 $0.00023 $0.00877
Sonnet 5 $0.00009 $0.00351
Haiku 4.5 $0.00005 $0.00176

Measured 2d ago against content hash 708eb495dbf8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

linear 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.

ironclaw/skills/linear/SKILL.md · 160 lines

How it starts

The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Linear API Skill

You have access to the Linear GraphQL API via the http tool. Credentials are automatically injected — never construct Authorization headers manually. When the URL host is api.linear.app, the system injects Authorization: {linear_api_key} transparently (no Bearer prefix — Linear API keys are sent raw).

Identity bootstrap (first use)

Linear's API key does not tell you who the user IS inside Linear. Before running any "my issues" / "assigned to me" / "my tickets" request, make sure the user's Linear identity is cached. This avoids re-fetching viewer on every request and makes filter-by-assignee queries deterministic.

Cache file

Path: context/intel/linear-identity.md

Shape:

---
type: linear-identity
bootstrapped_at: 2026-04-21
refreshed_at: 2026-04-21
stale_after: 2026-05-21
---
# Linear identity
user_id: 8a7f...-uuid
display_name: Tobias Holenstein
email: tobias@...
timezone: Europe/Zurich

## Teams
- id: team-uuid-a, key: ENG, name: Engineering
- id: team-uuid-b, key: PROD, name: Product

## Default team
ENG

Bootstrap flow

  1. memory_read("context/intel/linear-identity.md"). If the file exists and stale_after is in the future, use it and stop.
  2. If missing or stale, run one GraphQL call:
    query { viewer { id name displayName email } teams(first: 50) { nodes { id key name } } }
    
  3. Write the cache via memory_write with stale_after = today + 30 days.
  4. If the returned team list has exactly one team, record it as Default team. If more than one, ask the user once: "I see teams ENG, PROD, OPS. Which one do you default to for new issues?" and store the answer.
  5. On HTTP 401 or an AuthenticationError GraphQL error, invalidate the cache and re-prompt the user to check their API key — do not silently retry.

Using the cached identity

  • "list my issues" / "what's assigned to me" → filter by assignee: { id: { eq: "<cached user_id>" } }, not by assignee: { isMe: true } (the isMe filter is not universally available and viewer round-trips are wasteful).
  • "create an issue in my team" → use cached Default team id without asking.
  • "create an issue in " → match against cached team names; ask only if no match.
  • Skills that import external work into Linear must consume this cache rather than re-resolving identity per run.

Read the full file on GitHub · 160 lines

Changes

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.

  1. 2d ago First seen · 160 lines · 45 tokens per session scan A 708eb495dbf8

Subscribe to this mod's changes

linear is a skill published in the GitHub repository suyoumo/ClawProBench (823 stars, last pushed 8d ago), licensed Apache-2.0. It adds 45 tokens to every session and 1,755 once invoked, about $0.0002 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 2026-08-30.

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