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AD ai-builder-signal-digest

Create a transparent, sourced “Top 3–5” AI builder signal digest (weekly or date-range) from a list of links or from a local signals log; includes a short “why care” line per item and explicit maturity/adoption notes (e.g., GitHub stars/forks, paper-only). Use when preparing ClawHub Skill content or posts for the AI agent/tooling community.

ClawHub Agent Skills author: Guy Smith v1.0.0 MIT-0 4 files · 1 script body ≈ 446 tokens Open the sourceclawhub.ai↗ analyzed 7 d ago

Create a transparent, sourced “Top 3–5” AI builder signal digest (weekly or date-range) from a list of links or from a local signals log; includes a short…

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorGitHubAI and agentstype 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
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 48/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Steps. 13 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 446 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress

    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)
    • +3Output format is not stated: the model decides each time
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 342: enough signal without eating the budget
    • +4Structure: 4 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (2 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    The skill mostly does what it says, but its helper script can be tricked into fetching non-arXiv URLs from crafted input links.
    LLM: suspicious (medium) · VirusTotal: · 12 Sept 2026