camsnap

Capture frames or clips from RTSP/ONVIF cameras.

Quality

78%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

High

Do not use without reviewing

Fix and improve this skill with Tessl

tessl review fix ./skills/camsnap/SKILL.md

Quality

Content

100%

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

The body is an exemplar of a concise, actionable simple skill: real commands, no fluff, clear sections, and a diagnostic step. It fully meets the content rubric across all dimensions.

Dimension	Reasoning	Score
Conciseness	The body is lean across intro, Setup, Common commands, and Notes with no concept explanations or padding; every line earns its place.	3 / 3
Actionability	Commands are concrete and copy-paste ready with real flags and example values (e.g. 'camsnap snap kitchen --out shot.jpg', 'camsnap clip kitchen --dur 5s --out clip.mp4').	3 / 3
Workflow Clarity	As a simple single-action skill, its Setup→commands→Notes sequence is logical, the single actions are unambiguous, and 'camsnap doctor --probe' provides a diagnostic checkpoint.	3 / 3
Progressive Disclosure	Under 50 lines with no need for external references, it is organized into clear, well-labeled sections, which per the rubric warrants a 3.	3 / 3
	Total	12 / 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 is concrete and distinctive but lacks an explicit 'when to use' trigger clause and leans on technical protocol jargon, capping trigger quality and completeness at 2. It is a competent one-liner that would benefit from natural-language trigger terms and a Use-when clause.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user wants snapshots or clips from RTSP/ONVIF IP cameras.'

Replace or supplement the protocol jargon with natural terms users would say, such as 'snapshots', 'security cameras', 'IP cameras', or 'camera footage'.

Broaden the action list to match the body's full capability set (snapshots, clips, motion events) for greater comprehensiveness.

Dimension	Reasoning	Score
Specificity	Names the domain ('RTSP/ONVIF cameras') and concrete actions ('Capture frames or clips'), but it is essentially one verb with two objects and omits capabilities the body covers (snapshots, motion events), so it is not comprehensive.	2 / 3
Completeness	It clearly answers 'what' but contains no 'Use when...' or equivalent explicit trigger guidance, which per the rubric caps completeness at 2.	2 / 3
Trigger Term Quality	'frames', 'clips', and 'cameras' are natural terms, but 'RTSP/ONVIF' is protocol jargon and common variations like 'snapshots', 'security camera', 'IP camera', and 'footage' are missing.	2 / 3
Distinctiveness Conflict Risk	The niche—camera frame/clip capture via named protocols—is narrow and specific enough to be unlikely to conflict with unrelated skills.	3 / 3
	Total	9 / 12 Passed

Validation

81%

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 — 13 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
metadata_field	'metadata' should map string keys to string values	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	13 / 16 Passed

Repository: Bitterbot-AI/bitterbot-desktop
Path: skills/camsnap/SKILL.md
Commit: e73c717

Reviewed: about 14 hours ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.