BD en-tencent-novnc-chromium-cdp
One-click deploy remote visual browser — Linux noVNC + Chromium + CDP for headless servers, Windows direct Edge/Chrome CDP takeover. AI Agent and user share the same browser, manual CAPTCHA/QR-code/login fallback, never get stuck on automation walls.
One-click deploy remote visual browser — Linux noVNC + Chromium + CDP for headless servers, Windows direct Edge/Chrome CDP takeover.
As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 0. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 250 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - warning
body-longSKILL.md body ≈ 10930 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 43/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 68 mutating operations with no state check
- 40Execution cost. Instruction body is 10930 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 60Steps. 64 steps, 8 vague phrases
- 60Consistency. The Hermes dialect needs category and tags
- 100Failures and branches. 4 branches, has a failure section
- 100Progress reporting. Reports progress
- low 19 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (13 tags): a typed call is more reliable
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
- -2localhost URLs: will not work for another user
- -223 emoji in the instructions: noise for the model
- +2Single-language instructions
- +3Description length 250: enough signal without eating the budget
- +4Structure: 50 headings
- +3Step-by-step instructions: 64 items
- +4Has examples (51 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 53.