BF seo-blog-writer
Turn a single long-tail query into a publish-ready blog post that ranks in search and gets quoted by AI assistants. Runs the full pipeline: classify the topic, research it against real sources, draft clean HTML, scrub LLM-tell vocabulary and typography, audit for AI-SEO (TL;DR block, query-phrased H2s, FAQ section, FAQPage + BreadcrumbList + HowTo JSON-LD), then publish through a platform adapter (Ghost Admin API, WordPress REST, or static-site file output). Platform-agnostic core; swap the publish step without rewriting the writing pipeline. Built for indie hackers, founders, and content marketers who want AI to draft posts that are actually citable - not paraphrased docs, not hallucinated benchmarks. Trigger when the user says: 'write a blog post on X', 'draft an article about X', 'publish a post on X to Ghost / WordPress / the static site', or any request to ship editorial content for a long-tail query.
As a process F 56/100 · Will not run — References files that are not bundled: scripts/inject-glossary-links.py
The same skill appears in 1 more place: ClawHub
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 10434 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: scripts/inject-glossary-links.py - note
frontmatter-keyunknown frontmatter key "emoji" - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 56/100
- 0Tools and files. 1 referenced file(s) missing: scripts/inject-glossary-links.py
- 0Result and completion. Does not say what the result is
- 40Consistency. Frontmatter name (seo-blog-writer) differs from the folder (ghost-blog-writer)
- 40Execution cost. Instruction body is 10434 tokens: crowds the task out of the window
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 103 steps
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 13 branches, has a failure section
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 top-level sections: this looks like several domains in one skill
- high The skill tells the model to perform an irreversible action with no human approval
- low The response is described with custom markup (42 tags): a typed call is more reliable
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 919: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 44 headings
- +3Step-by-step instructions: 103 items
- +4Has examples (31 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.