SKILLEMALL.ai

AC task-tracker

Task-based cross-session context management for OpenClaw agents. Maintains persistent task files so context survives session resets, compaction, and channel switches. Use when: (1) A new task or project is discussed, (2) Progress or decisions are made on an existing task, (3) User says 'continue task', 'what is the status', 'where did we leave off', (4) A new session starts and user references prior work, (5) User mentions switching channels or losing context, (6) User asks about task status, progress, or next steps.

ClawHub Agent Skills author: Dylan Zhang v1.0.1 MIT-0 3 files body ≈ 650 tokens Open the sourceclawhub.ai analyzed 2 d ago

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

ReferenceInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
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

    ✓ No remarks against the Agent Skills spec

    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
    • 30Running it twice. 3 mutating operations with no state check
    • 40Consistency. Frontmatter name (task-tracker) differs from the folder (session-task-tracker)
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 21 steps
    • 100Execution cost. Instruction body is 650 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
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +3Description length 522: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 21 items
    • +4Has examples (3 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

    External checks

    ClawHub: clean
    This is a local task tracker that openly keeps persistent task notes, with privacy caveats but no evidence of hidden access, exfiltration, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026