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AC context-scope-tags

Use when: you chat across topics and want explicit boundaries to prevent topic bleed. Tags: [ISO], [SCOPE], [GLOBAL], [NOMEM], [REM]. (Memory tags are signals; persistence depends on your agent's memory backend.) Don't use when: you prefer free-form conversation where prior context carries over automatically. Output: a copy/paste tag cheat sheet + routing rules for how to treat the current message.

ClawHub Agent Skills author: phenomenoner v0.2.0 2 files body ≈ 774 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

ReferenceInfrastructureAI and agentsSoftware developmenttype 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
C
64/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "slug"

    Process rating: all ten parameters 64/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 70Failures and branches. 6 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 39 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 774 tokens
    • 100Running it twice. No mutating operations
    • low The response is described with custom markup (6 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
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 401: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 39 items
    • +4Has examples (0 code blocks)
    • +1License stated

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

    External checks

    ClawHub: clean
    This is an instruction-only chat tagging skill for scoping context and memory intent, with no executable behavior or hidden data access.
    LLM: benign (high) · VirusTotal: benign · 28 May 2026