BF whatsapp-monitor
Real-time WhatsApp message monitor that tracks specified chats or groups for keyword hits and periodically aggregates matching messages to a Feishu (Lark) multi-dimensional table. Use when: (1) You need to monitor WhatsApp conversations for specific keywords, (2) You want to collect filtered messages into a structured Feishu table, (3) You need scheduled batch reporting from WhatsApp to Feishu, (4) You're setting up automated message monitoring and alerting systems.
As a process F 40/100 · Will not run — References files that are not bundled: scripts/config.py, scripts/whatsapp_web.py, references/feishu_api.md
How to improve
- 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: 20. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Real-time WhatsApp message monitor that tracks specified chats or … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
missing-refreference to a missing file: scripts/config.py - warning
missing-refreference to a missing file: scripts/whatsapp_web.py - warning
missing-refreference to a missing file: references/feishu_api.md - warning
missing-refreference to a missing file: references/whatsapp_web.md - warning
missing-refreference to a missing file: references/filter_patterns.md
Process rating: all ten parameters 40/100
- 0Tools and files. 5 referenced file(s) missing: scripts/config.py, scripts/whatsapp_web.py, references/feishu_api.md
- 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. 7 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 100Steps. 74 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1897 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 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
- -42 reference files, but SKILL.md never points to them: the model will not open them
- -33 of 6 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 470: enough signal without eating the budget
- +4Structure: 43 headings
- +3Step-by-step instructions: 74 items
- +4Has examples (18 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.