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 navapbc/digital-service-orchestra --skill skill-refactorgit clone --depth 1 https://github.com/navapbc/digital-service-orchestraWrote 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/navapbc/digital-service-orchestra/skill-refactor)<a href="https://agentmods.dev/skills/navapbc/digital-service-orchestra/skill-refactor"><img src="https://agentmods.dev/badge/skills/navapbc/digital-service-orchestra/skill-refactor/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/navapbc/digital-service-orchestra/skill-refactor"><img src="https://agentmods.dev/badge/skills/navapbc/digital-service-orchestra/skill-refactor.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 | $0.00083 | $0.08742 |
| Opus 5.5 | $0.00033 | $0.03497 |
| Sonnet 5.5 | $0.00017 | $0.01748 |
| Haiku 4.5 | $0.00008 | $0.00874 |
Grade B, and why
skill-refactor scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
grep -rln "${s}" plugins/dso/ .claude/ tests/ docs/ 2>/dev/null | grep -v "^plugins/dso/scripts/${s%.sh}\.sh$" How it starts
The opening of the file, as written. The whole thing — 457 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Refactor
End-to-end token-efficiency and reliability pass on a DSO skill: review → approved plan → code/doc/test changes → ticket reconciliation → tessl review → committed result.
When to use
User signals: "review the X skill", "audit X", "can we optimize X?", "clean up X", "X is bloated", "X isn't reliable", or any request that implies critiquing a specific skill file and improving it.
Inputs
- Skill name (bare, no
dso:prefix) — e.g.,architect-foundation,brainstorm. - The skill's SKILL.md at
plugins/dso/skills/<name>/SKILL.md. - Any co-located phase files under
plugins/dso/skills/<name>/phases/or equivalent.
Workflow
The workflow is nine sequential phases. Do not skip. Phases A and B are synchronous with the user; Phases C–I execute autonomously once the plan is approved.
PA Critical review → present findings
PB Remediation plan → await explicit approval
PC Script relocation → move skill-scoped scripts to shared sub-dir
PD Reference updates → skill body, tests, docs
PE Change-detector test sweep → remove prose-grepping tests
PF Ticket reconciliation → comment on open tickets affected
PG Renumbering → renumber phases (A,B,C…) and steps (1,2,3…); update cross-skill refs
PH Tessl skill review → run tessl skill review; act on valid+actionable findings
PI Commit → via COMMIT-WORKFLOW.md; surface review findings
White elephants: phrasings to remove
A white elephant in a skill file is a phrasing that is intended to enforce a rule but instead creates the very temptation it forbids. The phrase names a bypass shape (cost-pressure, urgency-pressure, perceptual judgment) and then tells the agent to ignore it. The naming makes the bypass salient. White elephants are the symmetric counterpart to the "Hard gates: compress, do not remove" rule below: hard gates are load-bearing enforcement that must be preserved (compress only); white elephants are bypass-narration that should be removed entirely (the rule's positive form already does the enforcement work).
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.
- 2mo ago First seen · 457 lines · 83 tokens per session scan B eb9524be5141
skill-refactor is a skill published in the GitHub repository navapbc/digital-service-orchestra (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 83 tokens to every session and 8,742 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
skill-refactor compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| skill-refactornavapbc/digital-service-orchestra | Skill | 6 | yesterday | Apache-2.0 | B | 83 | Claude Code |
| imagegenopenai/codex | Skill | 135k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 100k | today | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 316k | 7d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |