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.
npx skills add dirtybits/agent-skills --skill software-development-workflowsgit clone --depth 1 https://github.com/dirtybits/agent-skillsWrote 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/skills/dirtybits/agent-skills/software-development-workflows)<a href="https://agentmods.dev/skills/dirtybits/agent-skills/software-development-workflows"><img src="https://agentmods.dev/badge/skills/dirtybits/agent-skills/software-development-workflows/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/skills/dirtybits/agent-skills/software-development-workflows"><img src="https://agentmods.dev/badge/skills/dirtybits/agent-skills/software-development-workflows.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 | $0.00044 | $0.01750 |
| Opus 5.5 | $0.00018 | $0.00700 |
| Sonnet 5.5 | $0.00009 | $0.00350 |
| Haiku 4.5 | $0.00004 | $0.00175 |
Grade A, and why
software-development-workflows 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Software Development Workflows
Overview
This umbrella covers the class-level software engineering practices that guide code work: planning, root-cause debugging, test-driven development, interactive debuggers, pre-commit review, simplification, and throwaway spikes.
It does not replace project-specific instructions. Always inspect the repository, its tests, and its conventions before applying generic recipes.
When to Use
- Debug failing tests, runtime bugs, build failures, or integration issues.
- Write tests before fixes or features.
- Use Python
pdb/debugpyor Node--inspectfor interactive diagnosis. - Run a pre-commit review or simplify a change set.
- Validate an uncertain technical approach with a spike.
- Author or adjust Hermes skill files.
Do not touch protected slash-command skills such as plan; when planning only, use the protected planning entry point if available.
Core Workflow
- Inspect before editing. Read relevant files, errors, configs, and tests.
- Reproduce. Run the smallest failing command and capture real output.
- Choose practice. Debugging, TDD, debugger attachment, review, simplification, or spike.
- Make minimal changes. Avoid broad refactors while fixing root causes.
- Verify. Run targeted tests first, then broader checks appropriate to the repo.
- Summarize with evidence. Report commands run, outputs, files changed, and residual risk.
Labeled Subsections from Former Narrow Skills
Systematic debugging
- No fixes before root cause. Read errors completely, reproduce, inspect recent changes, trace data flow, then form one hypothesis.
- If three attempted fixes fail, stop and question architecture instead of stacking a fourth patch.
Test-driven development
- RED: write or expose a failing test for the behavior.
- GREEN: implement the smallest root-cause fix.
- REFACTOR: clean only after tests prove behavior.
Python and Node debuggers
- Python: prefer targeted
pdb/debugpybreakpoints after reproducing the failure; avoid sprinkling permanent prints. - Node: use
--inspect/Chrome DevTools protocol only when normal logs/tests are insufficient; verify the debug target and port.
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- index.md 242 B
- LICENSE.txt 1.0 KB
- references/absorbed-packages/hermes-agent-skill-authoring/SKILL.original.md 7.8 KB
- references/absorbed-packages/node-inspect-debugger/SKILL.original.md 11 KB
- references/absorbed-packages/python-debugpy/SKILL.original.md 13 KB
- references/absorbed-packages/simplify-code/SKILL.original.md 8.7 KB
- references/absorbed-packages/spike/SKILL.original.md 8.9 KB
- references/absorbed-packages/systematic-debugging/SKILL.original.md 11 KB
- references/absorbed-packages/test-driven-development/SKILL.original.md 9.7 KB
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 · 112 lines · 44 tokens per session scan A 723bff33c00d
software-development-workflows is a skill published in the GitHub repository dirtybits/agent-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 1,750 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 skills, from other repositories
superpowers-zh
Use when constraining AI coding with Chinese TDD methodology, systematic debugging, code review, and verification workflows. Superpowers-zh: Chinese adaptation of the Superpowers AI-assisted programming skills and methodologies.
lsp-refactoring
Intelligent code refactoring using IDE-level tools (rename, find-references, go-to-definition), AST-aware pattern matching, and TDD verification. Use for safe, large-scale refactoring with precision.
tdd
A test-first development workflow that writes a failing test before the code, then makes it pass and improves the design.
debugging
Diagnose a failure, fix its root cause and verify the original scenario. Triggers on "debug", "调试".
code-quality-engineer
Consolidated code quality skill combining debugging, code review, and QA testing. Provides systematic root-cause analysis, architecture conformance checks, test strategy, and bug reporting. Ensures every feature meets quality bar. Combines: debugger + code-reviewer + qa-engineer.
test-design-reviewer
Evaluates test quality using Dave Farley's 8 properties. Use when reviewing tests, assessing test suite quality, or analyzing test effectiveness against TDD best practices.