SKILLEMALL.ai
GitHub ↗ RU Sign in

CA investigate

Systematic debugging with root cause investigation. (gstack)

The skillemall take

Promises systematic debugging with root cause investigation—think gstack for call stacks applied to code. Seven files, 12k tokens of content. Checks show code quality at 54, process at 83, safety at 95—no critical issues flagged. One medium-severity finding exists but remains unspecified in the data.

No model runs, no sandbox testing. Compatible across nine platforms: Claude, Cursor, DeepSeek, and others. Worth installing if you need a debugging analyzer and can validate it on your own examples before production use.

garrytan/gstack Agent Skills author: garrytan MIT 7 files body ≈ 12 293 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Systematic debugging with root cause investigation.

As a process A 83/100 · Runs to the end — weak spots: inputs and preconditions, execution cost

AnalyzerSoftware developmentAI and agentsResearchtype 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
79/100
safety, quality, tests
Safety 60%
95
Quality 40%
54
Run on models
none yet
Process rating
A
83/100
Runs to the end
Inputs and preconditions w 11
30
Execution cost w 6
40
Result and completion w 14
60
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 SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read Write Edit Grep Glob AskUserQuestion WebSearch

Files scanned: 7. 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 body-long SKILL.md body ≈ 12293 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "preamble-tier"
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "gbrain"
  • note edit-residue the text marks something as outdated (lines 468): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 83/100

  • 30Inputs and preconditions. Does not say what the process needs to start
  • 40Execution cost. Instruction body is 12293 tokens: crowds the task out of the window
  • 60Result and completion. Output format stated, no completion criterion
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 82 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 11 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 32 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (11 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
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 60: 120–800 characters recommended
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +4Structure: 40 headings
  • +3Step-by-step instructions: 82 items
  • +3Output format is stated explicitly
  • +4Has examples (21 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.