mathematical-logic-expert

Expert in formal logic, model theory, computability, and foundations of mathematics

Quality

46%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

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tessl review fix ./bundled/skills/mathematical-logic-expert/SKILL.md

Quality

Content

35%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a self-described 'legacy template awaiting research upgrade' that documents the skill's own validation status rather than delivering logic expertise, and every module it links to is missing. It is organized and lean but not actionable and does not function as progressive disclosure because the referenced files are absent.

Suggestions

Add the actual module files (modules/core-guidance.md, modules/known-gaps.md, modules/research-checklist.md, _toc.md) the body links to, or remove the broken references.

Replace the research-status meta-content with concrete, executable logic guidance (proof techniques, model-theoretic procedures, computability checks) so the skill is actionable on its own.

Move the time-sensitive 'Last validated: 2025-11-08' date into a clearly labeled deprecated/status section so it does not penalize the working content.

Dimension	Reasoning	Score
Conciseness	The body is short and lean, but it spends its tokens on meta-status ('Legacy template awaiting research upgrade', 'Confidence: Low') and an un-deprecated time-sensitive date ('2025-11-08') rather than logic content, matching 'mostly efficient but includes some unnecessary explanation or could be tightened'; the guideline penalizes time-sensitive dates not placed in a deprecated section.	2 / 3
Actionability	The guidance is abstract and points to files that do not exist ('Start with modules/research-checklist.md', 'Load topic-specific modules from _toc.md'), with no concrete code, commands, or actual logic instruction, matching the 'vague or abstract; no concrete code/commands; describes rather than instructs' anchor.	1 / 3
Workflow Clarity	A four-step sequence is listed under 'How to use this skill' with an implicit checkpoint ('only after verification'), but it is a maintenance workflow pointing at missing files with no real validation feedback loop, matching 'steps listed but validation gaps; sequence present but checkpoints missing or implicit'.	2 / 3
Progressive Disclosure	The body is organized into clearly signaled sections with markdown links to module files, but the referenced bundle (modules/*.md, _toc.md) does not actually exist on disk, so the disclosure structure is present in text yet non-functional, matching 'some structure but could be better organized; references present but not clearly signaled' with the broken references as the limiting factor.	2 / 3
	Total	7 / 12 Passed

Description

57%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description cleanly identifies a distinct, specific niche but reads as a capability label rather than an actionable trigger: it states what the skill is expert in without any 'Use when...' guidance or concrete actions. Adding an explicit trigger clause and named actions would lift completeness and specificity.

Suggestions

Add a 'Use when...' clause naming the situations that should activate this skill (e.g., formal proofs, model-theoretic arguments, computability questions).

Replace the static 'Expert in...' label with concrete actions the skill performs, such as 'Constructs and checks formal proofs, evaluates model-theoretic arguments, and reasons about computability.'

Include natural user-facing trigger phrasing alongside the technical terms so the skill fires on the way users actually phrase such requests.

Dimension	Reasoning	Score
Specificity	The phrase 'Expert in formal logic, model theory, computability, and foundations of mathematics' names several specific subfields but lists no concrete actions the skill performs, matching the 'names domain and some actions, but not comprehensive' anchor while falling short of the multi-action level-3 example.	2 / 3
Completeness	It states what the skill is ('Expert in...') but provides no 'Use when...' clause or equivalent trigger guidance, which per the judging guidelines caps completeness at 2 ('has what, but when is missing or only implied').	2 / 3
Trigger Term Quality	'formal logic, model theory, computability, and foundations of mathematics' are relevant niche keywords a user in this domain would plausibly say, but coverage is limited to technical jargon with no common variations or 'when...' phrasing, so it lands at 'some relevant keywords but missing common variations' rather than full natural-term coverage.	2 / 3
Distinctiveness Conflict Risk	The tightly scoped academic niche of formal logic, model theory, computability, and foundations of mathematics is clearly distinguishable and unlikely to trigger for unrelated skills, matching the 'clear niche with distinct triggers; unlikely to conflict' anchor.	3 / 3
	Total	9 / 12 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
relative_links	Relative link issues: 6 missing	Warning

	Total	15 / 16 Passed

Repository: foryourhealth111-pixel/Vibe-Skills
Path: bundled/skills/mathematical-logic-expert/SKILL.md
Commit: f627ab5

Reviewed: about 11 hours ago

Table of Contents

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