agentmods.dev

fix_feature_bug

fix_feature_bug is a skill for Claude Code, Codex from markmhendrickson/neotoma. It costs 7 tokens per session (716 once invoked), scanned A, a copy of fix-feature-bug, MIT.

A workflow for investigating and correcting a bug in a software feature or module. It reads project configuration and relevant specifications, then classifies the problem when classification rules are available.

In plain words
What is it for?
Use it to identify the affected feature, review its documentation, classify the bug, and apply the configured correction rules.
Why use it?
It provides a consistent path from an error to the right kind of change, including whether the code, specification, or other project material needs updating.

Skill for Claude CodeCodex

not rated 31 yesterday A scan 7 tokens copy · 91% MIT
View the source file markmhendrickson/neotoma
Install

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.

agentmods
npx agentmods add skills/markmhendrickson/neotoma/fix_feature_bug
Any agent
npx skills add markmhendrickson/neotoma --skill fix_feature_bug
Clone the repo
git clone --depth 1 https://github.com/markmhendrickson/neotoma

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for fix_feature_bug

README.md
[![agentmods](https://agentmods.dev/badge/skills/markmhendrickson/neotoma/fix_feature_bug.svg)](https://agentmods.dev/skills/markmhendrickson/neotoma/fix_feature_bug)
Your own site
<a href="https://agentmods.dev/skills/markmhendrickson/neotoma/fix_feature_bug"><img src="https://agentmods.dev/badge/skills/markmhendrickson/neotoma/fix_feature_bug.svg" alt="Measured on agentmods" height="20"></a>
Per session 7 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 716 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 91% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00007 $0.00716
Opus 5 $0.00003 $0.00358
Sonnet 5 $0.00001 $0.00143
Haiku 4.5 $0.00001 $0.00072

Measured 5d ago against content hash 4a6a3d5a9509, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

fix_feature_bug 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 5d 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.

Origin

This is a copy

91% identical to fix-feature-bug — 17 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/skills/fix_feature_bug/SKILL.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Fix Feature Bug

Fix a bug in a feature or module.

Configuration is read from foundation-config.yaml.

This workflow can also be triggered automatically via .claude/rules/bug_fix_detection.md (or foundation/agent_instructions/cursor_rules/bug_fix_detection.md) when you mention bug/error-related patterns in natural language (e.g., "bug", "error", "fix", "broken"). Both paths execute the same workflow.

Workflow

  1. Load configuration:

    • Read foundation-config.yaml for bug fix settings
    • Check if error classification is configured
    • Determine feature/module directory structure

  2. Identify feature/module from error, path, or context.

  3. Load relevant documents:

    • Repository navigation guide (if configured)
    • Feature/module spec and manifest (if available)
    • Error classification documentation (if configured)
    • Relevant subsystem/module documentation (if configured)

  4. Classify bug (if error classification configured):

    • Use configured error classification system
    • Determine correction approach based on class

  5. Apply correction rules:

    • If Class 1 (Implementation bug): Patch code only
    • If Class 2 (Spec bug): Update spec/manifest first, then align code/tests
    • If Class 3 (Architectural bug): Update subsystem/architecture docs first, then rebuild
    • If no classification: Fix bug and update relevant documentation

  6. Always add a regression test.

  7. Run tests:

    • Run configured test commands
    • Verify fix doesn't break existing functionality

  8. Output:

    • Error class (if classification configured)
    • Reason for classification
    • Corrected files
    • Tests added/updated

Error Classification (Configurable)

If development.bug_fix.error_classification.enabled: true in foundation-config:

  • Class 1: Implementation bug - spec is correct, code doesn't match spec
    • Action: Patch code only
  • Class 2: Spec bug - spec is incomplete or wrong, code matches spec but spec is wrong
    • Action: Update spec/manifest first, then align code/tests
  • Class 3: Architectural bug - subsystem/architecture docs are wrong or incomplete
    • Action: Update architecture docs first, then rebuild

Read the full file on GitHub · 95 lines

Changes

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.

  1. 5d ago First seen · 95 lines · 7 tokens per session scan A 4a6a3d5a9509

Subscribe to this mod's changes

fix_feature_bug is a skill published in the GitHub repository markmhendrickson/neotoma (31 stars, last pushed yesterday), licensed MIT. It adds 7 tokens to every session and 716 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to fix-feature-bug, differing in 17 lines, and is treated as a copy.

Debuggingagent-infrastructureagent-memoryai-agentsdeterministic-stateentity-resolutionevent-sourcing
Related

Other skills, from other repositories

security-observability

只读查询 agent-sec-cli 已落盘的历史安全事件记录，并据此生成会话级安全复盘。仅当用户显式要求查看或审计已发生的安全事件、安全告警、安全审计记录，或要求按 session/run/trace/时间/类别筛选与统计已有安全事件，或要求复盘某次会话的安全判定时使用。不用于扫描新内容：检查代码安全性用 code-scanner，检测 prompt 注入用 prompt-scanner，审查 Skill 安全状态用 skill-ledger。不要因为对话中出现“安全”“工具调用”等字样、或为了主动自查而触发。.

alibaba/anolisa · 145 tokens

add-backend

Guide for adding a backend (Rust or Python) to the agent-sec-core security middleware. Use when creating new backends, integrating Rust or Python code into the security middleware, or extending with new backend actions.

alibaba/anolisa · 46 tokens

skill-ledger

Skill 安全状态查看、风险暴露审查、用户决策、快速扫描认证与可选深度扫描。支持用户主动查看或扫描单个/全部 Skill；当用户要求 agent 安装 Skill 且安装成功后，必须自动对最终本地目录执行快速扫描认证。.

alibaba/anolisa · 67 tokens

pr-body

分析当前分支的全部变更，自动生成或更新 PR 标题和正文。聚焦内容质量：解释 why、归纳 what、标注测试方式，遵循 anolisa 项目 PR 模板规范。适用于新建 PR 前生成描述，或已有 PR 需要更新描述。.

alibaba/anolisa · 68 tokens

regex-mastery

Use this skill when writing regular expressions, debugging pattern matching,optimizing regex performance, or implementing text validation. Triggers on regex, regular expressions, pattern matching, lookahead, lookbehind, named groups, capture groups, backreferences, and any task requiring text pattern matching.

alibaba/anolisa · 60 tokens

install-openclaw

Install and configure OpenClaw non-interactively with Alibaba Cloud Model Studio. Use when the user asks to install OpenClaw, configure Aliyun Bailian/Model Studio/DashScope credentials, choose pay-as-you-go, Coding Plan, or Token Plan billing, set Base URL/model config, optionally configure DingTalk, start the local…

alibaba/anolisa · 85 tokens