Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/DailybotHQ/deepworkplan-skillnpx agentmods add commands/dailybothq/deepworkplan-skill/validate-frontmatterWrote 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/dailybothq/deepworkplan-skill/validate-frontmatter)<a href="https://agentmods.dev/commands/dailybothq/deepworkplan-skill/validate-frontmatter"><img src="https://agentmods.dev/badge/commands/dailybothq/deepworkplan-skill/validate-frontmatter/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/dailybothq/deepworkplan-skill/validate-frontmatter"><img src="https://agentmods.dev/badge/commands/dailybothq/deepworkplan-skill/validate-frontmatter.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 | $0.00018 | $0.00261 |
| Opus 5.5 | $0.00007 | $0.00104 |
| Sonnet 5.5 | $0.00004 | $0.00052 |
| Haiku 4.5 | $0.00002 | $0.00026 |
Grade A, and why
validate-frontmatter 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.
What it actually says
/validate-frontmatter
Run this repo's frontmatter validator — the same check CI enforces on every PR.
What to do
-
From the repo root, run:
python3 scripts/validate-frontmatter.py -
The validator scans every
SKILL.mdunderskills/(router + sub-skills + addon) and fails if any violates the conventions inAGENTS.md:name:is kebab-case and starts withdeepworkplanversion:is a quoted SemVer string- the legacy
homepage:key is absent (usedocumentation_url:) - frontmatter is delimited by
---markers
-
On failure, fix the offending
SKILL.mdfrontmatter and re-run until clean. Do not hand-editversion:to "fix" a check — the auto-release bot owns version numbers (seeAGENTS.md§4). If the validator flags an unquoted or malformed version, fix the quoting/format, not the number.
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 · 28 lines · 18 tokens per session scan A 3612c8d9d23d
validate-frontmatter is a command published in the GitHub repository DailybotHQ/deepworkplan-skill (23 stars, last pushed 3d ago), licensed MIT. It adds 18 tokens to every session and 261 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
kiro-validate-design
Command "kiro-validate-design" from gotalab/cc-sdd, covering technical design validation, core task, execution steps, important constraints and tool guidance.
autospec.plan
Generate YAML implementation plan from feature specification.
sddp-prd
Command description: Create or refine the canonical product document. Argument hint: [rough product idea, users, domain, or market opportunity] Command category: project-bootstrap Prerequisites: none.
cc-review
(Conductor) Review code changes against spec and standards.
sdd-setup
Onboarding wizard — DocLanguage, Memory Bank, architecture snapshot, working agreements (quality gate, TDD working mode), issue tracker.
wayfind
Plan a chunk of work too big for one agent session as a shared decision map: map.md + typed decision tickets in the mega-goal folder, resolved one per session through the kit's own grill/prototype/research machinery, until nothing is left to decide. Then hand off to /kit:spec or a ROADMAP, never straight to execute.