SKILLEMALL.ai

AB hybrid-training-plan

Read and update the user's own Hybrid Training Plan account (hybridtrainingplan.app) — today's and upcoming sessions with suggested weights, log strength sets, runs and rows, mark days complete or skipped, read and set exercise 1RMs. Use only when the user asks about their Hybrid Training Plan, their scheduled sessions, or wants a workout recorded there. Not for general fitness or training advice.

ClawHub Agent Skills author: Paul Kenneth Kent v1.1.0 MIT-0 4 files · 1 script body ≈ 916 tokens Open the sourceclawhub.ai↗ analyzed 14 d ago

Read and update the user's own Hybrid Training Plan account (hybridtrainingplan.app) — today's and upcoming sessions with suggested weights, log strength…

As a process B 68/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
99
Quality 40%
95
Run on models
none yet
Process rating
B
68/100
Nearly there
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Exfiltration net-credential-use scripts/htp.sh:23
      Credential used in a network call (verify the destination is the intended service) (detector / deny-list definition)
      printf 'Authorization: Bearer %s\n' "$API_KEY" | curl "${args[@]}" "$API_URL$path"
      detector

    Files scanned: 4. 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 68/100

    • 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. 4 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 7 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 916 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The response is described with custom markup (7 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

    • +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 400: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 7 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: clean
    This skill is a disclosed Hybrid Training Plan account helper that reads and updates workout data using a user-provided API key.
    LLM: benign (high) · VirusTotal: · 11 Oct 2026