SKILLEMALL.ai

AB handle-big-tasks

Instructions for breaking large tasks across multiple agentic runs instead of one response. Use when implementing a plan file, doing a large refactor, or any multi-phase task that won't fit in a single response. Covers the CONTINUE? Y or N and TASK COMPLETE! end-of-response markers, plus bash and CMD loop scripts that answer them automatically.

ClawHub Claude Code author: John Haugabook v1.0.0 MIT-0 4 files · 2 scripts body ≈ 2 081 tokens Open the sourceclawhub.ai↗ analyzed 9 d ago

Instructions for breaking large tasks across multiple agentic runs instead of one response.

As a process B 67/100 · Nearly there — weak spots: result and completion, running it twice

ProcedureGitHubSoftware developmentAI 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%
91
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
0
Running it twice w 4
30
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note edit-residue the text marks something as outdated (lines 112, 115, 123, 131): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 67/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 1 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 27 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2081 tokens
    • 100Progress reporting. Reports progress

    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
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 346: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 27 items
    • +4Has examples (8 code blocks)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: clean
    This skill coherently automates multi-phase coding work and clearly discloses that its optional loop scripts can keep Copilot running until the plan is complete.
    LLM: benign (high) · VirusTotal: · 9 Oct 2026