SKILLEMALL.ai

AA sentry-error-analyzer

Analyze Sentry error patterns, prioritize issues by user impact, identify root causes, and suggest targeted fixes. Use when asked to triage errors, analyze crash reports, or find the most impactful bugs to fix.

ClawHub Agent Skills author: charlie-morrison v1.0.0 MIT-0 2 files body ≈ 2 193 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process A 82/100 · Runs to the end — weak spots: when it triggers

AnalyzerData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
97
Quality 40%
87
Run on models
none yet
Process rating
A
82/100
Runs to the end
When it triggers w 12
20
Result and completion w 14
60
Inputs and preconditions w 11
70
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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Exfiltration net-credential-use SKILL.md:51
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
      curl -s -H "Authorization: Bearer $SENTRY_AUTH_TOKEN" \
      security skill
    • low Exfiltration net-credential-use SKILL.md:56
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
      curl -s -H "Authorization: Bearer $SENTRY_AUTH_TOKEN" \
      security skill
    • low Exfiltration net-credential-use SKILL.md:61
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
      curl -s -H "Authorization: Bearer $SENTRY_AUTH_TOKEN" \
      security skill

    Files scanned: 2. 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 82/100

    • 20When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 25 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2193 tokens
    • 100Running it twice. Mutating operations check current state
    • 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 210: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 25 items
    • +3Output format is stated explicitly
    • +4Has examples (7 code blocks)

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

    External checks

    ClawHub: clean
    This instruction-only skill helps analyze Sentry error data and its token/API examples are disclosed and aligned with that purpose.
    LLM: benign (high) · VirusTotal: · 29 May 2026