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AB content-refresher

Refresh old blog posts and outdated content with current statistics, new information, and freshness signals to restore search rankings. Use when the user asks to "update old content", "refresh content", "content is outdated", "improve declining rankings", "revive old blog posts", "traffic is declining on this page", "rankings dropped for this article", or "this post is outdated". For writing new content from scratch, see seo-content-writer. For auditing without rewriting, see on-page-seo-auditor.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 5 files body ≈ 3 766 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Refresh old blog posts and outdated content with current statistics, new information, and freshness signals to restore search rankings.

As a process B 66/100 · Nearly there — weak spots: failures and branches, running it twice, progress reporting

ProcedureGitHubWriting and documentsData and analyticsMarketingtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
96
Run on models
none yet
Process rating
B
66/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 66/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 5 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 49 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3766 tokens
    • low 10 top-level sections: this looks like several domains in one skill

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +3Description length 501: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 49 items
    • +3Output format is stated explicitly
    • +4Has examples (10 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.