Name: everlaw
Rating: 48 (1 reviews)
Author: membranedev

everlaw

Everlaw integration. Manage data, records, and automate workflows. Use when the user wants to interact with Everlaw data.

Quality

51%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

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

Quality

Content

45%Weight 40%Scale 1-5

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

The operational half of the skill is strong: executable CLI commands, clear auth/connection sequencing, and validation feedback loops. However, the massive 'Everlaw Overview' list—dominated by hallucinated 'AI …' buzzword entries—is severe padding that wrecks token efficiency and should be split into a separate reference file.

Suggestions

Remove the ~120 fabricated 'AI …' overview entries (e.g. 'AI Podcast Producers', 'AI Newsletter Editors') that are not real Everlaw entities and only consume context.

Move the remaining entity list into a separate references file (e.g. references/entities.md) and link to it one level deep from the body.

Keep the tight 'Working with Everlaw' CLI section as-is; it is the well-structured, actionable core of the skill.

Dimension	Reasoning	Score
Conciseness	The body is heavily padded: roughly 120 of the ~180 'Everlaw Overview' entries are 'AI …' buzzword items ('AI Podcast Producers', 'AI Newsletter Editors', 'AI Social Media Managers') that are not real Everlaw API entities, constituting severe verbosity and fluff.	1 / 5
Actionability	The 'Working with Everlaw' section provides concrete, copy-paste-ready bash commands for install, login, connection ensure, action list/run, and proxy requests with flag tables, covering the common cases with only minor placeholder gaps.	4 / 5
Workflow Clarity	The connection flow is clearly sequenced with explicit validation checkpoints (check state, poll with --wait until not BUILDING, branch on READY/CLIENT_ACTION_REQUIRED/CONFIGURATION_ERROR, re-poll after user action), giving a genuine feedback loop.	4 / 5
Progressive Disclosure	There are no bundle/reference files and the 180-line entity dump is inlined content that clearly belongs in a separate reference file, despite the 'Working with Everlaw' section having reasonable headers.	2 / 5
	Total	11 / 20 Passed

Description

57%Weight 40%Scale 1-5

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 clearly identifies the Everlaw niche and includes an explicit 'Use when' trigger, but its action language is generic and buzzword-laden rather than reflecting concrete eDiscovery capabilities. Trigger keyword coverage is limited to the product name itself.

Suggestions

Replace generic actions with concrete Everlaw capabilities, e.g. 'Search and review documents, build productions, and manage matters in Everlaw.'

Add natural synonyms users say such as 'eDiscovery', 'litigation', or 'legal document review' to broaden trigger coverage.

Make the 'Use when' clause more specific, e.g. 'Use when the user wants to search, review, or produce documents in Everlaw.'

Dimension	Reasoning	Score
Specificity	The domain (Everlaw) is named and it lists 'Manage data, records, and automate workflows', but these actions are generic and buzzword-y rather than concrete Everlaw capabilities like searching documents, reviewing batches, or building productions.	2 / 5
Completeness	It explicitly answers both 'what' ('Manage data, records, and automate workflows') and 'when' ('Use when the user wants to interact with Everlaw data'), though the 'what' is generic and the 'when' could be more specific.	4 / 5
Trigger Term Quality	It includes the natural product keyword 'Everlaw' and 'Everlaw data', but misses common variations and synonyms a user might say such as eDiscovery, litigation, legal documents, or case review.	3 / 5
Distinctiveness Conflict Risk	Naming a specific unique product (Everlaw) gives it a clear niche with minimal conflict risk, though the generic 'manage data, records, and automate workflows' phrasing creates minor overlap risk with broad data-management skills.	4 / 5
	Total	13 / 20 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
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: membranedev/application-skills
Path: skills/everlaw/SKILL.md
Commit: f484c82

Reviewed: ~19 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.