SKILLEMALL.ai

DC start-1-1

Module 1.1: Welcome to TaskFlow. Introduces TaskFlow, the course structure, and Codex for PM work.

The skillemall take

The module promises an introduction to TaskFlow and course structure for PMs. Files contain 5 documents totaling 3313 tokens, no scripts. Checks found two high-severity concealment issues: the skill hides parts of its logic or dependencies. Scores: quality 67, process 60, safety 64—middling with clear gaps. Model run and sandbox tests skipped.

This is introductory material with no active functionality, but hidden elements in the structure raise flags. Skip it: unclear what's being concealed, and that matters for a learning module.

Not recommendedcritical or high security findings · low grade D
carlvellotti/claude-code-pm-course Agent Skills author: carlvellotti 5 files body ≈ 3 313 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Module 1.1: Welcome to TaskFlow. Introduces TaskFlow, the course structure, and Codex for PM work.

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

ProcedureAsanaJiraLearningSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
D
65/100
safety, quality, tests
Safety 60%
64
Quality 40%
67
Run on models
none yet
Process rating
C
60/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Concealment
If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 2

  • high Concealment en-hide-from-user SKILL.md:9
    Instruction to hide actions from the user
    At the start of this lesson, silently copy the bundled lesson assets into the workspace if they are not already present. Do not show command output to the student.
  • high Concealment en-hide-from-user SKILL.md:15
    Instruction to hide actions from the user
    Before greeting the learner: silently run `fspm progress`. If it shows a learner name, greet them by it and continue. If it shows no name and no declined marker, run `fspm onboard` and follow the tour

Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 60/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Result and completion. Does not say what the result is
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 85Steps. 90 steps, 1 vague phrases
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3313 tokens
  • 100Running it twice. Mutating operations check current state

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)
  • +3Description length 98: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -216 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 90 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.