SKILLEMALL.ai

AC failure-registry

Search the Agent Failure Registry for known agent failures, solutions, and lessons learned. Use when encountering errors, debugging issues, or wanting to learn from other agents' documented post-mortems. Also supports submitting new failure post-mortems via GitHub PR.

ClawHub Agent Skills author: unleashedbelial v0.1.0 10 files · 1 script body ≈ 1 012 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceGitHubAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
95
Quality 40%
87
Run on models
none yet
Process rating
C
54/100
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • medium Exfiltration intent-browser-credential-store examples/belial-twitter-cookie-expiry.yaml:26
      Accesses a browser credential / cookie store (test fixture / example file)
      Request fresh cookies from human operator.
      fixture

    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 54/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 40Consistency. Frontmatter name (failure-registry) differs from the folder (agent-failure-registry)
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 48 steps
    • 100Execution cost. Instruction body is 1012 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 268: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 48 items
    • +4Has examples (3 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: suspicious
    This is a coherent failure-registry search skill, but it includes actionable advice for bot-detection evasion and raw social-media session cookie reuse that users should review before installing.
    LLM: suspicious (high) · VirusTotal: benign · 28 May 2026