Reference standards for writing and maintaining GitHub issues in the tldraw repository. Use as supporting guidance when another skill or workflow needs issue title, body, type, label, or triage standards.
npx skills add https://github.com/tldraw/tldraw --skill write-issue
Standards for issues in tldraw/tldraw.
Bug:, Feature:, [Bug], etc.Arrow bindings break with rotated shapesAdd padding option to zoomToFit methodPinch zoom resets selection on SafariBug: arrow bug (prefix, vague)[Feature] Add new feature (prefix, vague)Not working (vague)Bug: X → XAdd Padding Option → Add padding optionAdding feature X → Add feature XProblem → [Describe the actual problem]Set via the GitHub GraphQL API after creating the issue (the --type flag is not reliably supported):
| Type | Use for |
| --------- | ----------------------------------- |
| Bug | Something isn't working as expected |
| Feature | New capability or improvement |
| Example | Request for a new SDK example |
| Task | Internal task or chore |
Use sparingly (1-2 per issue) for metadata, not categorization.
| Label | Use for |
| ------------------ | -------------------------------- |
| good first issue | Well-scoped issues for newcomers |
| More Info Needed | Requires additional information |
| sdk | Affects the tldraw SDK |
| dotcom | Related to tldraw.com |
| a11y | Accessibility |
| performance | Performance improvement |
| api | API change |
keep, stale, update-snapshots, publish-packages, major, minor, skip-release, deploy triggers
Issues created by the /issue skill capture the user's intent over a short interrogation, so they carry an unheaded readback paragraph beneath the verbatim description, followed by open questions and a confidence status line at the bottom:
Critical: is genuinely blocking — the issue cannot be worked on until it is answered. Most issues have none. Non-critical questions the user chooses not to answer are marked _Deferred by user; not blocking implementation._.Confidence: 84%, ready to get started. or Confidence: 42%, still need more information. It reflects whether the issue has enough of the user's intent and context to work on, not confidence in the eventual fix.Leave the readback, open questions, and confidence line in the issue once interrogation is complete. The answered questions are a record of the discussion that produced the issue, so keep them rather than deleting them — mark questions resolved in place and keep the final readback as the issue's concise problem statement.
More Info Needed label and comment if details missinggood first issue if appropriatekeep label if should remain openAutomatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing. Uses GPT-5.2 by default for state-of-the-art software engineering.
Implement memory-safe programming with RAII, ownership, smart pointers, and resource management across Rust, C++, and C. Use when writing safe systems code, managing resources, or preventing memory bugs.
Python/HTSlib workflows for genomic files. Use when reading, querying, filtering, or writing SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, or tabix data with pysam, including pileup, coverage, indexing, and CRAM references.
Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.
Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL.
> Create, build, deploy, and localize declarative agents for M365 Copilot and Teams. USE THIS SKILL for ANY task involving a declarative agent — including localization, scaffolding, editing manifests, adding capabilities, and deploying. Localization requires tokenized manifests and language files that only this skill knows how to produce. "scaffold an agent", "new agent project", "add a capability", "add a plugin", "configure my agent", "deploy my agent", "fix my agent manifest", "edit my agent", "localize my agent", "add localization", "translate my agent", "multi-language agent", "add an API plugin", "add an MCP plugin", "add OAuth to my plugin", "review instructions", "improve instructions", "fix my instructions"
Documentation generation workflow covering API docs, architecture docs, README files, code comments, and technical writing.
Take tldraw/write-issue from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.