SKILLEMALL.ai

AC purrplan

Drive PurrPlan (social media scheduler) from your agent — plan, draft, schedule and publish posts across 12+ networks (LinkedIn, X, Instagram, TikTok, Facebook, YouTube, Threads, Bluesky…), manage the unified inbox and read analytics, via PurrPlan's remote MCP server. Use when the user wants to schedule social posts, fill a content calendar, reply to comments/DMs, or check social performance.

ClawHub Agent Skills author: Sébastien De Bollivier v1.0.0 MIT-0 2 files body ≈ 632 tokens Open the sourceclawhub.ai analyzed 3 d ago

Drive PurrPlan (social media scheduler) from your agent — plan, draft, schedule and publish posts across 12+ networks (LinkedIn, X, Instagram, TikTok…

As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorYouTubeMarketingAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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: 2. 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 62/100

    • 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
    • 30Running it twice. 5 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 14 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 632 tokens

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 395: enough signal without eating the budget
    • +4Structure: 4 headings
    • +3Step-by-step instructions: 14 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This skill coherently connects an agent to PurrPlan for social scheduling, inbox replies, and analytics, with the main risks being normal credential and publishing risks that users should handle carefully.
    LLM: benign (high) · VirusTotal: · 3 Sept 2026