SKILLEMALL.ai

AC clankerhive

Shared SQLite-backed context store for multi-session agent coordination. Use when: (1) checking if work was already done recently (email checked, briefing sent), (2) preventing duplicate cron/heartbeat runs via task claiming, (3) passing alerts between sessions (cron queues alert → main session pops it), (4) storing short-lived facts with TTL, or (5) any cross-session state sharing. Replaces ad-hoc JSON state files with a proper coordination bus. Triggers on: deduplication, cross-session state, shared facts, alert queue, task coordination, heartbeat state.

ClawHub Agent Skills author: Paul Frederiksen v1.0.3 MIT-0 3 files body ≈ 1 338 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ReferenceAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 52/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 8 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1338 tokens
    • 100Running it twice. Mutating operations check current state

    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 562: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 8 items
    • +4Has examples (11 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: clean
    ClankerHive is a disclosed local coordination store for sharing agent state, with real privacy and stale-data risks but no hidden or unrelated behavior found.
    LLM: benign (high) · VirusTotal: · 29 May 2026