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CD mastra-smoke-test

Smoke test Mastra projects locally or deploy to staging/production. Tests Studio UI, agents, tools, workflows, traces, memory, and more. Supports both local development and cloud deployments.

mastra-ai/mastra Agent Skills author: mastra-ai NOASSERTION 31 files · 3 scripts body ≈ 3 970 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Smoke test Mastra projects locally or deploy to staging/production.

As a process D 47/100 · Unfinished process — References files that are not bundled: references/tests/*.md

ProcedureGitHubInfrastructureData and analyticsAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
84/100
safety, quality, tests
Safety 60%
93
Quality 40%
71
Run on models
none yet
Process rating
D
47/100
Unfinished process
References files that are not bundled: references/tests/*.md
Tools and files w 18
0
Result and completion w 14
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
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 · 3

✓ No critical or high findings

Medium and low: 3
  • medium Broad scope meta-agent-memory-dump references/tests/memory.md
    Agent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokens
    references/tests/memory.md
  • low Exfiltration read-dotenv references/tests/setup.md:271
    Reads a .env file
    cat .env | grep API_KEY
  • low Exfiltration read-dotenv references/tests/setup.md:298
    Reads a .env file (documentation table row)
    | Env vars             | `cat .env`                |
    table

Files scanned: 31. 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")
  • warning missing-ref reference to a missing file: references/tests/*.md

Process rating: all ten parameters 47/100

Will not run. References files that are not bundled: references/tests/*.md
  • 0Tools and files. 1 referenced file(s) missing: references/tests/*.md
  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 21 mutating operations with no state check
  • 65Failures and branches. 3 branches
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 20 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3970 tokens
  • low 12 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
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 191: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (10 code blocks)
  • +4Reference files are cited in the instructions (15 of 15)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.