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AD axiom-hash-multi

Multi-algorithm hash generator (MD5/SHA-1/SHA-256/SHA-512/BLAKE2b) — deterministic, byte-to-byte, zero dependencies. Use when you need to hash a file or string with multiple algorithms at once, with no LLM, no cloud, no hallucination.

ClawHub Agent Skills author: Kofna3369 v1.1.3 MIT-0 10 files body ≈ 719 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Multi-algorithm hash generator (MD5/SHA-1/SHA-256/SHA-512/BLAKE2b) — deterministic, byte-to-byte, zero dependencies.

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorSoftware developmentAI 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
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
D
46/100
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: 10. 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 46/100

    • 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
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 100Steps. 20 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 719 tokens
    • 100Running it twice. No mutating operations

    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)
    • +3Output format is not stated: the model decides each time
    • -217 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 234: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 20 items
    • +4Has examples (2 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: clean
    This skill is a straightforward local hash utility that reads user-selected inputs and does not show hidden network, credential, persistence, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 15 Jun 2026