SKILLEMALL.ai

BC session-tracker

Checkpoints multi-step work to disk so a crashed or dropped session can be resumed rather than redone. Use when a task has two or more steps AND writes files or generates code AND losing mid-task state would be costly; when resuming after a session drop; or when the user asks for crash-resilient tracking. Do not use for single-step tasks, read-only analysis, trivial lookups, exploratory conversation, or anything involving credentials or paths that should not persist. Writes JSON state to .session/ only: task name, step list, agent-declared file paths, worklog entries — never file contents. Filesystem scanning is off by default; status does not scan unless --fs-scan is passed. No network, no eval, no environment harvesting. Optional opt-in extras: a detached 24h-bounded monitor, and a cross-session journal. Restored content is fenced and labelled as untrusted data. cleanup is irreversible and requires an ownership marker plus --force.

ClawHub Agent Skills author: DarkD v2.6.1 MIT-0 9 files · 4 scripts body ≈ 2 129 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Checkpoints multi-step work to disk so a crashed or dropped session can be resumed rather than redone.

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureSoftware developmentPersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
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: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "permissions"
    • note edit-residue the text marks something as outdated (lines 140): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 60/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 6 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
    • 100Steps. 31 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2129 tokens
    • 100Progress reporting. Reports progress
    • low 10 top-level sections: this looks like several domains in one skill

    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
    • +3Description length 947: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 31 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 1 scripts are documented

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

    External checks

    ClawHub: clean
    The skill is a disclosed local crash-recovery tracker that stores task progress on disk, with some operational caveats around where state is written and cleanup is run.
    LLM: benign (medium) · VirusTotal: · 19 Sept 2026