SKILLEMALL.ai

AC hizal-end

Close the agent's context session and consolidate what was learned. Self-triggering — fires when the agent finishes a task, wraps up work, or is about to go idle. Handles the keep/promote/discard review of surfaced memory chunks. Triggers on phrases like "I'm done", "that's it for now", "wrapping up", "let me commit and close out", "finished this task", or any time the agent is ending a work session.

ClawHub Agent Skills author: Parker v0.1.0 MIT-0 2 files body ≈ 292 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
58/100
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 58/100

    • 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. 1 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 70When it triggers. States when to use, but not when not to
    • 75Steps. 3 steps
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 292 tokens
    • high The skill tells the model to perform an irreversible action with no human approval

    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 403: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 3 items
    • +4Has examples (3 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: suspicious
    This skill is coherent, but needs review because it can auto-run at session wrap-up and modify or delete stored memory without explicit confirmation.
    LLM: suspicious (high) · 28 May 2026