CC research-supervisor-pro
EVE — Persistent AI Research Supervisor Agent. Three modes: Auto, Semi-Manual, Manual. Full research lifecycle from search to publication-ready LaTeX paper.
As a process C 63/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 7
✓ No critical or high findings
Medium and low: 7
-
medium Exfiltration
net-redirectable-api-keyscripts/build_survey.py:33Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
-
medium Exfiltration
net-redirectable-api-keyscripts/gap_detector.py:33Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
-
medium Exfiltration
net-redirectable-api-keyscripts/idea_generator.py:33Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
-
medium Exfiltration
net-redirectable-api-keyscripts/paper_writer.py:36Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
-
low Secrets in code
secret-password-literalscripts/build_survey.py:190Hard-coded password / key literal (may be an example)api_key = sys.argv[4] if len(sys.argv) > 4 else None
-
low Secrets in code
secret-password-literalscripts/gap_detector.py:147Hard-coded password / key literal (may be an example)api_key = sys.argv[2] if len(sys.argv) > 2 else None
-
low Secrets in code
secret-password-literalscripts/idea_generator.py:139Hard-coded password / key literal (may be an example)api_key = sys.argv[2] if len(sys.argv) > 2 else None
Files scanned: 25. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 3, column 14: description: EVE — Persistent AI Research Supervisor Agent. Three modes: Auto, … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
body-longSKILL.md body ≈ 7769 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 63/100
- 20When it triggers. No condition that starts the skill
- 30Inputs and preconditions. Does not say what the process needs to start
- 40Consistency. Frontmatter name (research-supervisor-pro) differs from the folder (eve-research-supervisor-pro)
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Execution cost. Instruction body is 7769 tokens
- 100Steps. 81 steps
- 100Failures and branches. 6 branches, has a failure section
- 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 19 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 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)
- -4Absolute local paths (C:\Users, /home/…): not portable
- -237 emoji in the instructions: noise for the model
- -32 of 18 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 156: enough signal without eating the budget
- +4Structure: 60 headings
- +3Step-by-step instructions: 81 items
- +3Output format is stated explicitly
- +4Has examples (66 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.