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Get Started Free →Repo-specific triage guidance for warp. Only the categories declared overridable by the core triage-issue skill may be specialized here.
.claude/skills/warpdotdev-triage-issue-local/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 175% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 144% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 148% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 103% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 175% | 0% |
warpThis skill specializes the core triage-issue skill (named in the specializes frontmatter field) and is not functional on its own. Before applying its guidance, confirm the parent skill is installed and resolvable at .agents/skills/triage-issue/SKILL.md. If it is missing, install it first by copying the skill directory from the source declared in the specializes_source frontmatter field (warpdotdev/oz-for-oss:.agents/skills/triage-issue). Then continue with the guidance below.
This file is a companion to the core triage-issue skill. It does not redefine the triage output schema, safety rules, or follow-up-question contract. It only specializes the override categories the core skill marks as overridable.
warp is the public-facing Warp desktop client repository. Treat public issue reports as potentially incomplete and avoid asking for secrets, tokens, private workspace names, private repository names, or account identifiers in the public issue thread.area:billing or area:auth label as appropriate so the issue is still routed correctly.agent:bug, agent:feature, agent:security, agent:documentation), except billing or appeals reports which route to support via warp:needs-support. Explicitly bias towards tagging regressions ("broke in recent version", "worked in previous build"), panics/crashes, and security reports with agent:priority-high.Ask at most 2 follow-up questions per triage response. Each question must be high-value: it should meaningfully change the label assignment, owner routing, or reproduction confidence if answered. Do not ask questions whose answers can be inferred from existing evidence, and do not bundle multiple sub-questions into a single bullet. If more than 2 unknowns exist, prioritize the two that are most likely to unblock triage.
The label taxonomy for this repository is managed in .github/issue-triage/config.json. Prefer labels from that configuration, especially the area:*, os:*, repro:*, accessibility, needs-info, duplicate, agent:priority-high, and primary agent issue-type labels (agent:bug, agent:feature, agent:security, agent:documentation). Do not invent new labels unless the prompt explicitly allows it.
Every issue should be classified with at least one primary agent type label:
agent:bug: Bugs/regressions. Assigned by Warp triage agent.agent:feature: This issue is a feature request, not a bug report. Assigned by Warp triage agent.agent:security: Security issues/vulnerabilities that are immediately escalated. Assigned by Warp triage agent.agent:documentation: Missing documentation. Assigned by Warp triage agent.agent:priority-high: High-priority issues that are immediately escalated. Assigned by Warp triage agent. Tag issues with agent:priority-high when there is evidence of a regression ("broke in recent version", "worked in previous build"), panic or crash, data loss, or a security vulnerability.Evaluate ready-to-implement during triage instead of relying on issue-template defaults. For bug reports, apply ready-to-implement only when the issue is reproducible from the provided evidence or straightforward local verification and the likely fix appears narrow enough to implement without a product spec, design mocks, or substantial investigation. If the bug is not reproducible, lacks a clear fix path, requires product/design decisions, or needs deeper technical discovery, omit ready-to-implement and prefer needs-info, ready-to-spec, needs-mocks, or the appropriate repro:* label.
Use area labels based on the user's reported surface:
area:shell-terminal for terminal output, block rendering, shell integration, prompt rendering, command execution display, and terminal-emulation behavior.area:terminal-input for command-line input editing, cursor movement, key handling, and typed text behavior.area:window-tabs-panes for window, tab, pane, split, layout, and focus behavior.area:editor-notebooks for editors, notebooks, markdown rendering, LSP, and code display.area:agent for agent conversations, agent mode, cloud/local agent execution, prompts, and AI-specific UI.area:code-review for git diff views, review UI, review comments, and PR-focused agent flows.area:mcp for MCP server connection, tool/resource discovery, OAuth, and integration issues.area:settings-keybindings for settings UI, preferences, keyboard shortcuts, and keybinding configuration.area:warp-drive for Warp Drive objects, sync, sharing, workflows, notebooks, tab configs, and persisted artifacts.area:performance:* when the report includes CPU, memory, GPU, startup, rendering, latency, or responsiveness symptoms. Add the more specific CPU, memory, or GPU label when the evidence points to that resource.Before asking the reporter for more information, check the issue body, comments, attachments, logs, labels, and repository context for:
Prefer .github/STAKEHOLDERS for owner inference. When no path-level match exists, use the label and issue surface to choose likely owners rather than defaulting to broad app ownership.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 8,677 | 9,356 | +8% | 1 | 1 | 0% | 1,317 | 3,616 | +175% | 0 | 0 | — |
case-02 | fail→pass | 7,361 | 6,888 | -6% | 1 | 1 | 0% | 1,212 | 2,959 | +144% | 0 | 0 | — |
case-03 | fail→pass | 11,053 | 12,008 | +9% | 1 | 1 | 0% | 1,611 | 3,990 | +148% | 0 | 0 | — |
case-04 | fail→pass | 10,285 | 10,354 | +1% | 1 | 1 | 0% | 1,465 | 2,978 | +103% | 0 | 0 | — |
case-05 | fail→pass | 7,542 | 17,667 | +134% | 1 | 1 | 0% | 1,150 | 3,163 | +175% | 0 | 0 | — |
case-06 | fail→pass | 6,778 | 5,695 | -16% | 1 | 1 | 0% | 968 | 3,036 | +214% | 0 | 0 | — |
case-07 | fail→pass | 15,603 | 5,631 | -64% | 1 | 1 | 0% | 1,448 | 2,925 | +102% | 0 | 0 | — |
case-08 | fail→pass | 5,534 | 22,189 | +301% | 1 | 1 | 0% | 679 | 2,534 | +273% | 0 | 0 | — |
case-09 | fail→pass | 12,679 | 8,090 | -36% | 1 | 1 | 0% | 1,871 | 3,163 | +69% | 0 | 0 | — |
case-10 | fail→pass | 9,331 | 7,114 | -24% | 1 | 1 | 0% | 1,121 | 3,281 | +193% | 0 | 0 | — |
case-11 | fail→pass | 13,463 | 8,888 | -34% | 1 | 1 | 0% | 2,210 | 3,419 | +55% | 0 | 0 | — |
case-12 | fail→pass | 5,656 | 10,335 | +83% | 1 | 1 | 0% | 696 | 3,814 | +448% | 0 | 0 | — |
case-13 | pass→pass | 7,023 | 4,068 | -42% | 1 | 1 | 0% | 918 | 2,557 | +179% | 0 | 0 | — |
case-14 | pass→pass | 13,417 | 4,992 | -63% | 1 | 1 | 0% | 1,825 | 2,731 | +50% | 0 | 0 | — |
case-15 | pass→pass | 9,044 | 7,619 | -16% | 1 | 1 | 0% | 1,207 | 3,245 | +169% | 0 | 0 | — |
case-16 | fail→pass | 18,816 | 7,010 | -63% | 1 | 1 | 0% | 1,389 | 2,592 | +87% | 0 | 0 | — |
case-17 | pass→pass | 8,836 | 4,141 | -53% | 1 | 1 | 0% | 1,208 | 2,649 | +119% | 0 | 0 | — |
case-18 | pass→pass | 8,250 | 5,988 | -27% | 1 | 1 | 0% | 1,233 | 2,864 | +132% | 0 | 0 | — |
case-19 | pass→pass | 11,173 | 9,751 | -13% | 1 | 1 | 0% | 1,661 | 3,157 | +90% | 0 | 0 | — |
case-20 | fail→pass | 17,339 | 11,157 | -36% | 1 | 1 | 0% | 2,583 | 3,953 | +53% | 0 | 0 | — |
case-21 | fail→pass | 19,488 | 52,311 | +168% | 1 | 1 | 0% | 3,627 | 5,864 | +62% | 0 | 0 | — |
case-22 | fail→pass | 6,475 | 11,811 | +82% | 1 | 1 | 0% | 199 | 4,178 | +1999% | 0 | 0 | — |
case-23 | fail→pass | 16,537 | 53,649 | +224% | 1 | 1 | 0% | 2,324 | 4,620 | +99% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted, and 22 counted toward the lift figure. The other 1 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +74 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.