SKILLEMALL.ai

AA linkedin-reply-handler

Draft a reply to a specific existing LinkedIn comment from its URL. Use when the user wants to reply to a comment on any post, or follow up after an author replied to them. Parses the commentUrn, resolves the correct parentComment target (LinkedIn flattens threads to 2 levels), and posts via Publora on approval. Not for top-level comments (use linkedin-comment-drafter).

ClawHub Agent Skills author: Sergey Bulaev v1.0.9 MIT-0 5 files body ≈ 1 215 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process A 83/100 · Runs to the end — weak spots: running it twice, progress reporting

GeneratorInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
A
83/100
Runs to the end
Progress reporting w 2
0
Running it twice w 4
30
Result and completion w 14
60
the three weakest of ten parameters · all ten

How to improve

    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: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 83/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 4 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Failures and branches. 7 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 28 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1215 tokens
    • low The response is described with custom markup (4 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
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 372: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 28 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (2 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: clean
    This skill drafts and posts LinkedIn replies with user approval, and its reaction behavior is disclosed rather than hidden.
    LLM: benign (high) · VirusTotal: · 9 Jul 2026