src/autoskillit/skills_extended/report-bug/SKILL.md
Investigate a bug from provided error context, write a structured markdown report to the given path, and output a deduplication fingerprint. Lightweight — no parallel subagents.
npx skillsauth add talont-org/autoskillit report-bugInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Perform a targeted bug investigation from a provided error context and produce a structured report. This skill is intentionally lightweight — it performs a directed codebase search rather than spawning parallel subagents, so it stays fast enough for non-blocking pipeline use.
The prompt will contain:
Error context:
<error message, traceback, or free-form description>
Report output path: /absolute/path/to/report.md
NEVER:
ALWAYS:
Extract from the prompt:
error_context: everything under "Error context:"report_path: the absolute path after "Report output path:"From the error context:
KeyError, AssertionError, TypeError)Use Grep and Read to locate the relevant callsite and understand the surrounding logic:
Keep searches focused — 3–5 targeted queries is sufficient.
Synthesise a canonical bug description of ≤ 80 characters that uniquely identifies the bug class (not the specific stack frame). This is used for GitHub deduplication.
Format: <ErrorType> in <module>: <one-line cause>
Examples:
KeyError in recipe/validator.py: missing ingredient ref in step captureAssertionError in execution/headless.py: runner=None before session startUse the Write tool to write the structured report to the exact path from the prompt.
Report template:
# Bug Report
**Date:** {YYYY-MM-DD}
**Error type:** {error type}
**Affected module:** {file path}
## Error Context
{verbatim error_context}
## Callsite
**File:** {file}:{line}
**Function:** {function name}
## Root Cause Hypothesis
{1–3 sentences explaining the likely root cause}
## Relevant Code
```python
{the failing function or the surrounding ~10 lines}
{Concise next step — e.g. "Check X before Y", "Add guard for Z condition"}
### Step 6: Output the Fingerprint Block
After writing the report file, output the following in your response text so the
calling tool can extract it for GitHub deduplication:
---bug-fingerprint--- {the fingerprint from Step 4} ---/bug-fingerprint---
Then confirm: `Report written to {report_path}`
development
Generate YAML recipes for .autoskillit/recipes/. Use when user says "make script skill", "generate script", "script a workflow", "write a script", "create a script", "new recipe", "write a pipeline", or when loaded by other skills for script formatting.
data-ai
Create Uncertainty Representation visualization planning spec showing error bar definitions, distribution-aware alternatives, and multi-seed variance protocols. Statistical lens answering "How is uncertainty honestly represented?"
data-ai
Create Temporal Dynamics visualization planning spec showing axis scaling (linear vs log), smoothing disclosure, epoch/step alignment, run aggregation (mean + variance bands), early-stopping markers, and wall-clock vs step-count x-axis. Temporal lens answering "Are training dynamics shown clearly and honestly?"
data-ai
Create Narrative Story Arc visualization planning spec showing visual consistency across the report (same color = same model everywhere), logical figure progression, redundant figure detection, and narrative dependency between figures. Narrative lens answering "Do the figures tell a coherent story across the report?"