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.
git clone --depth 1 https://github.com/RoniLeor/specWeaverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/ronileor/specweaver/feature-bugfix)<a href="https://agentmods.dev/commands/ronileor/specweaver/feature-bugfix"><img src="https://agentmods.dev/badge/commands/ronileor/specweaver/feature-bugfix/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/ronileor/specweaver/feature-bugfix"><img src="https://agentmods.dev/badge/commands/ronileor/specweaver/feature-bugfix.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.06572 |
| Opus 5.5 | $0.00018 | $0.02629 |
| Sonnet 5.5 | $0.00009 | $0.01314 |
| Haiku 4.5 | $0.00005 | $0.00657 |
Grade A, and why
feature:bugfix 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 1,159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bug Fix Command: Systematic Bug Resolution Workflow
This command provides a structured approach to investigating and fixing bugs in existing features through deep code analysis, solution research, and phased implementation with review gates.
Command Structure
The bugfix workflow follows these phases:
- Phase 0: Bug Investigation (Parallel Analysis)
- Phase 1: Bug Clarification (User Confirmation)
- Phase 2: Solution Research (4 Parallel Web Searches)
- Phase 3: Solution Design (User Approval Required)
- Phase 3.5: Design Review (code-reviewer)
- Phase 4: Phased Implementation (Review Gates)
- Phase 5: Regression Testing (User Verification)
- Phase 6: Documentation Update (After Fix Confirmed)
Core Principle
⚠️ CRITICAL: Read the code carefully before designing new solutions - the existing implementation often already handles edge cases. Understanding what's already there prevents duplicate solutions and unnecessary complexity.
Spec File Structure
All specifications are stored in:
.claude/specs/bugfix-{feature-name}/
├── 00-investigation.md # Bug investigation findings
├── 01-bug-report.md # User-confirmed bug details
├── 02-research.md # Solution research findings
├── 03-solution-design.md # Fix strategy and phases
├── 03-design-review.md # Design review feedback
├── phase-{X}-{name}.md # Atomic fix phase specs
└── phase-{X}-{name}-review.md # Phase implementation reviews
Phase Execution
Phase 0: Bug Investigation (Parallel Analysis)
CRITICAL: This phase uses PARALLEL execution for efficiency.
Execute in SINGLE message with TWO Task tool calls:
Task 1: Deep Code Analysis
Task tool with subagent_type: "code-reviewer"
Prompt: "Analyze the {feature-name} feature to identify potential bugs.
ANALYSIS REQUIREMENTS:
1. Code Design Understanding:
- Break down code into atomic components
- Understand intended design and architecture
- Map dependencies and data flow
- Identify critical execution paths
2. Line-by-Line Investigation:
- Analyze each function for logic errors
- Check error handling and edge cases
- Verify type safety and null checks
- Look for race conditions and timing issues
- Check resource management (memory, files, connections)
3. Common Bug Patterns:
- Off-by-one errors
- Null/undefined references
- Type mismatches
- Incorrect conditionals
- Missing error handling
- Resource leaks
- Concurrency issues
4. Potential Bug Locations:
- Identify suspicious code sections
- Flag code smells and anti-patterns
- Note areas with high complexity
- Highlight recent changes (if in git history)
Return DETAILED findings with:
- File paths and line numbers
- Code snippets of suspicious sections
- Explanation of potential issues
- Severity rating (Critical/High/Medium/Low)"
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.
- 1mo ago First seen · 1,159 lines · 45 tokens per session scan A f8a4906a5142
feature:bugfix is a command published in the GitHub repository RoniLeor/specWeaver (3 stars, last pushed 11mo ago), licensed MIT. It adds 45 tokens to every session and 6,572 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
Other commands, from other repositories
perf
Structured performance investigation with baselines, profiling, and evidence-backed decisions.
bug-fix
Streamlines bug fixing by creating a GitHub issue first, then a feature branch for implementing and thoroughly testing the solution before merging.
cleanup
You are executing the /dogma:cleanup command. Your task is to find and fix AI-typical patterns in the codebase that reveal AI/agent usage.
lint
You are executing the /dogma:lint command. Your task is to detect the project type and run appropriate linting and formatting tools on staged files before commit.
ship
Complete PR workflow from commit to production with validation.
audit-project-agents
This file contains detailed agent coordination for /audit-project.