BD evolution-api-v2
Complete WhatsApp automation via Evolution API v2.3 - instances, messages (text/media/polls/lists/buttons/status), groups, labels, chatbots (Typebot/OpenAI/Dify/Flowise/N8N/EvoAI), webhooks, proxy, S3 storage, and Chatwoot integration
Complete WhatsApp automation via Evolution API v2.3 - instances, messages (text/media/polls/lists/buttons/status), groups, labels, chatbots…
As a process D 45/100 · 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.
- 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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Exfiltration
exfil-webhook-urlSKILL.md:147Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)"url": "https://webhook.site/your-id",
placeholder -
low Exfiltration
exfil-webhook-urlSKILL.md:934Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)"url": "https://webhook.site/your-id",
placeholder
Files scanned: 1. 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
body-longSKILL.md body ≈ 8929 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 45/100
- 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
- 30Running it twice. 46 mutating operations with no state check
- 40Consistency. Frontmatter name (evolution-api-v2) differs from the folder (evolution-api)
- 40Execution cost. Instruction body is 8929 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 100Steps. 42 steps
- 100Failures and branches. 2 branches, has a failure section
- low 10 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)
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +3Description length 234: enough signal without eating the budget
- +4Structure: 128 headings
- +3Step-by-step instructions: 42 items
- +4Has examples (101 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.