CD sharpagent-intelligence-monitor
SharpAgent Intelligence Monitor — Multi-track parallel intelligence aggregation system. Auto-collects from RSS/arXiv/GitHub/36kr, 3D dynamic scoring, five-factor trust verification, structured briefing output. For daily intelligence summaries, tech trend tracking, and competitive monitoring.
SharpAgent Intelligence Monitor — Multi-track parallel intelligence aggregation system.
As a process D 48/100 · Unfinished process — References files that are not bundled: {Link}
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: {Link}
Process rating: all ten parameters 48/100
- 0Tools and files. 1 referenced file(s) missing: {Link}
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 29 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2155 tokens
- 100Progress reporting. Reports progress
- low 11 top-level sections: this looks like several domains in one skill
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)
- -259 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 292: enough signal without eating the budget
- +4Structure: 29 headings
- +3Step-by-step instructions: 29 items
- +3Output format is stated explicitly
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.