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AD file-hasher

Compute, verify, and compare file hashes using MD5, SHA-1, SHA-256, SHA-512, and more. Use when checking file integrity, verifying downloads against expected checksums, comparing files for equality, generating checksums for directories, hashing strings, or validating checksum files (sha256sum/md5sum format). Supports BSD and standard output formats, JSON output, multi-algorithm hashing, and recursive directory scanning. No external dependencies.

ClawHub Agent Skills author: John Wang v1.0.0 MIT-0 3 files body ≈ 522 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Compute, verify, and compare file hashes using MD5, SHA-1, SHA-256, SHA-512, and more.

As a process D 38/100 · Unfinished process — weak spots: steps, result and completion, when it triggers

AnalyzerSoftware 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
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
D
38/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
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: 3. 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 38/100

    • 0Steps. Prose only: no discrete steps
    • 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
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 522 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)
    • +3No numbered steps or checklist
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 449: enough signal without eating the budget
    • +4Structure: 10 headings
    • +4Has examples (8 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This is a straightforward local file-hashing helper with no evidence of hidden network access, persistence, credential use, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026