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Agent skill

Linear Performance Tuning

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Improve Linear GraphQL latency and throughput by reducing field, connection, pagination, and polling cost.

MITAuto-check passedBackend & APIs

Install Linear Performance Tuning

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill linear-performance-tuning -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace linear-performance-tuning --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/linear-performance-tuning .claude/skills/linear-performance-tuning && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
linear-performance-tuning
GitHub stars
2.8k
Token cost
~1.2k tokens
SKILL.md length
499 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Improve Linear GraphQL latency and throughput by reducing field, connection, pagination, and polling cost.

  • Works in 6 steps: Measure operation latency, requested… → Replace broad SDK model walks with a… → Filter at the server, request the… → …
  • Queries are slow
  • SKILL.md covers Overview, Prerequisites, Tool Discipline and Current Contract, plus 7 more sections
  • Needs API_KEY and ACCESS_TOKEN

What it does

Linear Performance Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. Improve Linear GraphQL latency and throughput by reducing field, connection, pagination, and polling cost. Use when queries are slow, complex, or exhausting shared budgets. Trigger with "optimize Linear GraphQL", "reduce Linear query complexity", or "speed up Linear sync".

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/official-docs.md`). Compatibility notes: Designed for Claude Code; live verification requires network access and an approved Linear workspace credential

It sits in Backend & APIs, covering GraphQL. It works with GraphQL. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Queries are slow
  • Exhausting shared budgets
  • With optimize Linear GraphQL
  • Reduce Linear query complexity

Example prompts

  • “optimize Linear GraphQL”
  • “reduce Linear query complexity”
  • “speed up Linear sync”
  • “/linear-performance-tuning”

Requirements

  • A credential in API_KEY
  • A credential in ACCESS_TOKEN
  • Compatibility (from SKILL.md): Designed for Claude Code; live verification requires network access and an approved Linear workspace credential
  • Pre-approved tools (allowed-tools): Read, Glob, Grep, WebFetch, Write, Edit

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Measure operation latency, requested fields, connection fan-out, page sizes, complexity header, payload bytes, and cache hit rate.
  2. Replace broad SDK model walks with a purpose-built GraphQL query when only a narrow projection is needed.
  3. Filter at the server, request the smallest explicit page, and paginate until hasNextPage is false.
  4. Eliminate N+1 reads and uncoordinated polling; use webhooks plus a bounded reconciliation window.
  5. Load-test below the applicable shared request/complexity budgets and verify tail latency and correctness.
  6. Document before/after evidence and rollback the query change if semantics or visibility differ.

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Glob
    • Grep
    • WebFetch
    • Write
    • Edit

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • linear.app

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • API_KEY
    • ACCESS_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code; live verification requires network access and an approved Linear workspace credential

    From compatibility in the SKILL.md frontmatter.

Context cost

Linear Performance Tuning loads about 1.2k tokens when it runs, and up to ~2k if it reads all its reference files. Until then it costs about 75 tokens; SKILL.md has 499 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~75
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 499 words, ~1,217 tokens.

Download SKILL.mdSave it as .claude/skills/linear-performance-tuning/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
linear-performance-tuning
description
Improve Linear GraphQL latency and throughput by reducing field, connection, pagination, and polling cost. Use when queries are slow, complex, or exhausting shared budgets. Trigger with "optimize Linear GraphQL", "reduce Linear query complexity", or "speed up Linear sync".
allowed-tools
Read, Glob, Grep, WebFetch, Write, Edit
compatibility
Designed for Claude Code; live verification requires network access and an approved Linear workspace credential
argument-hint
[repository-path] [operation-name]
version
1.13.0
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
tags
saas, linear, performance
model
inherit
effort
high

Linear Query Performance Tuning

Overview

Tune the measured operation rather than applying guessed delays, and preserve correctness with bounded pagination and reconciliation.

Prerequisites

  • The target repository, Linear workspace, environment, and accountable owner
  • Current security, privacy, compliance, capacity, and change-control requirements
  • An approved Linear credential only when a bounded live verification is necessary

Tool Discipline

Use Read, Glob, and Grep to inspect code, configuration, and evidence. Use WebFetch only for current first-party Linear documentation and package metadata. Use Write or Edit only for requested implementation with known target files. Never write credentials, customer content, unrestricted environment output, or unredacted GraphQL variables.

Current Contract

  • Each property costs 0.1 complexity point, each object 1 point, and connections multiply child cost by the requested page size or default 50, rounded up.
  • A single query cannot exceed 10,000 complexity points; hourly complexity and request limits are shared by user or app actor.
  • Filtering server-side, requesting explicit page sizes, ordering by updated time, and using webhooks reduce unnecessary work.

Authentication

Use a personal API key only for owner-controlled scripts, OAuth with PKCE for user-delegated applications, or an enabled client-credentials grant for approved automation. Personal keys use Authorization: <API_KEY>; OAuth tokens use Authorization: Bearer <ACCESS_TOKEN>. Store credentials server-side in an approved secret manager.

Treat app approval, team access, scope changes, credential creation, rotation, revocation, and production access as owner-approved actions.

Instructions

  1. Measure operation latency, requested fields, connection fan-out, page sizes, complexity header, payload bytes, and cache hit rate.
  2. Replace broad SDK model walks with a purpose-built GraphQL query when only a narrow projection is needed.
  3. Filter at the server, request the smallest explicit page, and paginate until hasNextPage is false.
  4. Eliminate N+1 reads and uncoordinated polling; use webhooks plus a bounded reconciliation window.
  5. Load-test below the applicable shared request/complexity budgets and verify tail latency and correctness.
  6. Document before/after evidence and rollback the query change if semantics or visibility differ.
Show full SKILL.md (181 more words)Show less

Approval Boundaries

Do not create, reveal, rotate, or revoke credentials; authorize an OAuth app; change scopes or team access; create, mutate, archive, or delete workspace data; configure or re-enable webhooks; import or export data; change roles, SCIM, or audit streaming; transmit diagnostics; change paid entitlements; or perform another production mutation without explicit approval from the accountable owner. Keep diagnosis read-only unless implementation was requested.

Output

Return the workspace and team scope, auth mode without credential value, files and contracts inspected, exact operation names, evidence collected, validation result, sensitive fields redacted, remaining risk, accountable owner, approval state, and rollback or next action.

Error Handling

ConditionResponse
Complexity above 10,000Shrink connections, fields, or page size before sending the query.
Budget exhaustedCoordinate producers and wait for reset metadata; do not spin retries.
Pagination misses dataUse stable cursors and explicit updated-time reconciliation.
Cache leaks visibilityScope keys by workspace/team/access context or disable the cache.

Examples

Use a compact handoff that makes scope, mutation authority, and verification evidence reviewable.

Input:

text
operation=IssueSync; first=50; nested-connections=3; complexity=measured

Expected handoff:

text
query=narrowed; pagination=cursor; polling=replaced; correctness=verified

Resources

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/.curated/linear-performance-tuning of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/official-docs.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Linear Performance Tuning next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Linear Performance Tuning compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Linear Performance Tuning this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.2kAutomated safety check: PassMIT
Nodejs Backend Patternsever-works/ever-works16218 repos~4kAutomated safety check: PassAGPL-3.0
API DesignerJeffallan/claude-skills12k1 repos~2kAutomated safety check: PassMIT
GraphQL Operations with CodegenChrisWiles/claude-code-showcase6.1k3 repos~1.5kAutomated safety check: PassNone
API Design Principlesjh941213/my-cc-harness12518 repos~3.4kAutomated safety check: PassNone
API And Interface Designdzhalaevd/Donatello1358 repos~2.6kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Linear Performance Tuning

What does Linear Performance Tuning do?

Improve Linear GraphQL latency and throughput by reducing field, connection, pagination, and polling cost. Linear Performance Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. Improve Linear GraphQL latency and throughput by reducing field, connection, pagination, and polling cost.

When should I use Linear Performance Tuning?

Linear Performance Tuning fits situations like: queries are slow; exhausting shared budgets; with optimize Linear GraphQL; reduce Linear query complexity.

How do I install Linear Performance Tuning in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill linear-performance-tuning -a claude-code`. Or copy the skill folder (skills/.curated/linear-performance-tuning in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/linear-performance-tuning in your project. Claude Code loads it when a task matches its description.

How do I install Linear Performance Tuning in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill linear-performance-tuning -a codex`. Or copy the skill folder (skills/.curated/linear-performance-tuning in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/linear-performance-tuning in your project. Codex loads it when a task matches its description.

Can I use Linear Performance Tuning in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill linear-performance-tuning -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linear-performance-tuning, .gemini/skills/linear-performance-tuning, .github/skills/linear-performance-tuning and .opencode/skills/linear-performance-tuning in your project.

What does Linear Performance Tuning need to run?

Going by SKILL.md and its folder, Linear Performance Tuning needs credentials named API_KEY and ACCESS_TOKEN. Our summary lists: A credential in API_KEY; A credential in ACCESS_TOKEN. Its frontmatter pre-approves these tools: Read, Glob, Grep, WebFetch, Write, Edit. Compatibility (from SKILL.md): Designed for Claude Code; live verification requires network access and an approved Linear workspace credential.

Does Linear Performance Tuning access the network?

SKILL.md names 1 domain. As links in the text: linear.app. This is read from the text; nothing was executed.

Is Linear Performance Tuning safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Linear Performance Tuning use?

Linear Performance Tuning is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Linear Performance Tuning use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 817 tokens, read only when the agent opens those files.

What are the alternatives to Linear Performance Tuning?

Skills that share tags, products or a category with Linear Performance Tuning: Nodejs Backend Patterns (ever-works/ever-works, 162 stars), API Designer (Jeffallan/claude-skills, 12k stars), GraphQL Operations with Codegen (ChrisWiles/claude-code-showcase, 6.1k stars) and API Design Principles (jh941213/my-cc-harness, 125 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Linear Performance Tuning?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.