Name: social-media-analyzer
Rating: 64 (1 reviews)
Author: alirezarezvani

social-media-analyzer

Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use when analyzing social media performance, calculating engagement rate, measuring campaign ROI, comparing platform metrics, or benchmarking against industry standards. Also use when the user mentions "social media audit," "engagement rate," or "which platform performs best."

Quality

77%

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Securityby

Passed

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tessl review fix ./.gemini/skills/social-media-analyzer/SKILL.md

The canonical home for this skill is social-media-analyzer in alirezarezvani/claude-skills

Quality

Content

63%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.

A well-structured, mostly actionable analysis skill with clear sequenced workflows and validation checkpoints. Its weaknesses are repeated formulas and an unfulfilled progressive-disclosure promise: all referenced bundle files are missing while their contents are partly duplicated inline.

Suggestions

Remove duplicated formulas — keep the engagement-rate and ROI formulas in only one place (the definition/formula tables) and delete the redundant code-block restatements.

Either provide the referenced bundle files (references/platform-benchmarks.md, scripts/calculate_metrics.py, scripts/analyze_performance.py, assets/sample_input.json, assets/expected_output.json) or drop the references and keep content inline to avoid broken navigation.

Add an explicit validate→fix→retry feedback loop to the Analysis Workflow (e.g., 'If validation fails, correct the input data and re-run validation before proceeding') to earn the workflow-clarity anchor 5.

Dimension	Reasoning	Score
Conciseness	Mostly compact table-driven content with genuinely useful domain data (benchmark percentages, value estimates), but formulas are repeated (engagement rate at lines 79 and 86; ROI at lines 112 and 117) and the 'Reference Documentation' section restates benchmark content already shown inline, so it could be tightened.	3 / 5
Actionability	Provides concrete executable commands ('python scripts/calculate_metrics.py assets/sample_input.json'), specific formulas, and a copy-paste-ready sample input/output pair; the main gap is reliance on scripts for the actual computation rather than inline code.	4 / 5
Workflow Clarity	Both the Analysis Workflow and ROI Calculation are clearly numbered sequences with explicit validation steps and a pre-analysis checklist, but there is no validate→fix→retry feedback loop describing error recovery, so it falls short of anchor 5.	4 / 5
Progressive Disclosure	Structure is good (table of contents, clear sections, one-level-deep reference to references/platform-benchmarks.md), but the referenced bundle files (references/, scripts/, assets/) do not exist, so the navigation promise is unfulfilled, and inline benchmark tables overlap with the referenced file.	3 / 5
	Total	14 / 20 Passed

Description

91%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.

A strong description: third-person voice, explicit what-and-when structure, and rich natural trigger terms including quoted user utterances. The only soft spot is slight overlap risk with adjacent analytics skills rather than a uniquely owned niche.

Dimension	Reasoning	Score
Specificity	Lists several concrete actions — 'Calculates engagement rates, ROI, and benchmarks across platforms' plus 'campaign analysis and performance tracking' — but stops short of the comprehensive multi-action coverage of the anchor 5 example.	4 / 5
Completeness	Explicitly states both what ('Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks') and when ('Use when analyzing... Also use when the user mentions...') with concrete trigger phrases, matching the anchor 5 example.	5 / 5
Trigger Term Quality	Covers natural phrases users would say ('social media performance', 'engagement rate', 'campaign ROI', 'benchmarking') plus quoted trigger utterances like 'social media audit' and 'which platform performs best', giving comprehensive synonym/variation coverage.	5 / 5
Distinctiveness Conflict Risk	The social-media-analysis niche is clear with distinct triggers, but there is minor overlap risk with closely related marketing skills (e.g., campaign-analytics, noted in the body) rather than the minimal conflict of anchor 5.	4 / 5
	Total	18 / 20 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning
referenced_paths_exist	Referenced path issues: 8 missing	Warning

	Total	14 / 16 Passed

Repository: alirezarezvani/claude-skills
Path: .gemini/skills/social-media-analyzer/SKILL.md
Commit: 19392f7

Reviewed: ~17 hours ago

Table of Contents

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