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Local and remote desktop observation/input tools with coordinate normalization, application targeting and honest place receipts (local macOS/Linux by default; optional OSWorld HTTP and SSH Mac backends).

razzant/ouroboros Agent Skills author: razzant 5 files · 4 scripts body ≈ 6 425 tokens Open the sourcegithub.com↗ analyzed 9 h ago

Local and remote desktop observation/input tools with coordinate normalization, application targeting and honest place receipts (local macOS/Linux by default…

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmenttype 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
D
76/100
safety, quality, tests
Safety 60%
100
Quality 40%
41
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

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 · 0

✓ No critical or high findings

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

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 6425 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "type"
  • note frontmatter-key unknown frontmatter key "entry"
  • note frontmatter-key unknown frontmatter key "plugin_api"
  • note frontmatter-key unknown frontmatter key "runtime"
  • note frontmatter-key unknown frontmatter key "os"
  • note frontmatter-key unknown frontmatter key "permissions"
  • note frontmatter-key unknown frontmatter key "env_from_settings"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "model_experience"
  • note edit-residue the text marks something as outdated (lines 9): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 54/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 30Running it twice. 9 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70Execution cost. Instruction body is 6425 tokens
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 36 steps
  • 100Consistency. Name and required fields are in place
  • 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 (3 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)
  • +4Structure: 1 headings, hard to scan
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -5Long text without headings
  • +1No license
  • +2Single-language instructions
  • +3Description length 203: enough signal without eating the budget
  • +3Step-by-step instructions: 36 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 41.