medication-adherence-message-gen

Use medication adherence message gen for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries.

Quality

41%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./scientific-skills/Academic Writing/medication-adherence-message-gen/SKILL.md

Quality

Content

50%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 body contains genuinely actionable usage material (CLI, API, output examples) but is diluted by substantial templated boilerplate and a verbatim re-statement of the mismatched description. Workflow guidance is present but generic, and progressive disclosure is only partially realized with most content inlined.

Suggestions

Remove the redundant boilerplate sections (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status, Response Template) and the verbatim description repeats to tighten the body.

Replace the self-referential stubs ('See `## Usage` above') with the actual content or delete them.

Integrate the py_compile Quick Check into the Workflow as an explicit validation step before running scripts/main.py, so the sequence has a concrete checkpoint.

Dimension	Reasoning	Score
Conciseness	The body is noticeably verbose: it repeats the mismatched frontmatter description verbatim (lines 20, 26), includes self-referential stubs ('See `## Prerequisites` above'), and pads in generic boilerplate (Risk Assessment, Security Checklist, Lifecycle Status, Response Template) that is not specific to medication-adherence messaging.	2 / 5
Actionability	The Usage section provides concrete, copy-paste-ready guidance: a CLI options table, runnable example commands, a Python API snippet, and sample text/JSON output formats covering the common cases.	4 / 5
Workflow Clarity	A 5-step Workflow and 4-step run plan are listed, but the steps are generic ('confirm objective', 'validate request', 'return structured result') and the py_compile Quick Check is not integrated as an explicit validation checkpoint within the workflow.	3 / 5
Progressive Disclosure	There is section structure and one clearly signaled one-level reference (references/audit-reference.md, which exists), but large blocks of content (options table, templates, generic checklists) are inlined in SKILL.md rather than split out, leaving organization only partly effective.	3 / 5
	Total	12 / 20 Passed

Description

32%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 is templated boilerplate that restates the skill name and frames it as 'academic writing workflows,' which does not match the skill's real purpose of generating behavioral-psychology medication reminder messages. It is vague on capabilities and supplies an incorrect use-context, weakening trigger quality and distinctiveness.

Suggestions

Rewrite the description to state the real capability, e.g. 'Generates SMS/push medication-reminder copy using behavioral psychology principles (social norms, loss aversion, implementation intentions).'

Add a correct 'Use when...' clause tied to the actual task: 'Use when creating patient medication adherence reminders, refill nudges, or dosage-timing notifications.'

Drop the generic 'structured execution / explicit assumptions / clear output boundaries' phrasing, which is filler that conflicts with academic-writing skills.

Dimension	Reasoning	Score
Specificity	The description names the domain ('medication adherence message gen') but the only actions offered are generic boilerplate ('structured execution, explicit assumptions, and clear output boundaries') rather than concrete capabilities like generating SMS/push reminder copy.	2 / 5
Completeness	It states a vague 'what' (just restating the skill name) and a 'when' that points to the wrong domain ('academic writing workflows'), so neither half concretely and correctly answers what the skill does or when to invoke it.	2 / 5
Trigger Term Quality	'medication adherence message' is a relevant clinical keyword, but the surrounding trigger context ('academic writing workflows', 'structured execution') is mismatched to the skill and the natural user terms ('medication reminder', 'SMS', 'patient notification') are absent.	3 / 5
Distinctiveness Conflict Risk	The generic 'academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries' framing is broad and would overlap with many writing-skills, while the actual medication-reminder niche is not signaled by the trigger phrasing.	2 / 5
	Total	9 / 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: aipoch/medical-research-skills
Path: scientific-skills/Academic Writing/medication-adherence-message-gen/SKILL.md
Commit: 63c61d3

Reviewed: 12 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.