SKILLEMALL.ai

AC perstate

A git-native remote knowledge graph that provides persistent state for agents and individuals. /perstate checks status, /perstate save writes insights, /perstate search recalls, /perstate fork copies branches, /perstate switch changes branches, /perstate info shows stats, /perstate view visualizes, /perstate prune cleans up. Trigger: user says "persist" "remember" "recall" "memory" "save insight" or types /perstate. Auto-extracts insights, deduplicates and merges, multi-hop queries, graph visualization.

ClawHub Agent Skills author: Florian v1.1.0 MIT-0 14 files · 10 scripts body ≈ 3 620 tokens Open the sourceclawhub.ai analyzed 3 d ago

A git-native remote knowledge graph that provides persistent state for agents and individuals.

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions

GeneratorSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
50
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 55/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 50When it triggers. No condition that starts the skill
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 85Steps. 22 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3620 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (21 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

    • +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
    • +5Description quotes 5 example trigger phrases
    • +3Description length 508: enough signal without eating the budget
    • +4Structure: 24 headings
    • +3Step-by-step instructions: 22 items
    • +4Has examples (12 code blocks)
    • +3All 10 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.

    External checks

    ClawHub: suspicious
    This is a coherent git-backed memory skill, but it needs review because it can persist conversation-derived knowledge locally and remotely with broad triggers and limited consent controls.
    LLM: suspicious (high) · 20 Jul 2026