AC linkedin
LinkedIn automation skill — search people and companies, fetch profiles, send messages and InMails, manage connections, create posts, react, comment. Supports Sales Navigator.
As a process C 53/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency
This is a copy of a skill from another catalog; the rating counts the canonical one: linkedin (ClawHub)
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 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")
Process rating: all ten parameters 53/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 8 mutating operations with no state check
- 40Consistency. Frontmatter name (linkedin) differs from the folder (linkedin-skill)
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Execution cost. Instruction body is 4010 tokens
- 100Steps. 22 steps
- 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 175: enough signal without eating the budget
- +4Structure: 34 headings
- +3Step-by-step instructions: 22 items
- +3Output format is stated explicitly
- +4Has examples (46 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.
External checks
ClawHub: suspicious
This LinkedIn automation skill is disclosed, but it gives an agent broad power to message, post, change connections, run workflows, and handle account tokens without enough safety boundaries.
LLM: suspicious (high) · VirusTotal: suspicious · 28 May 2026