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estimate-analysis

Deep-dive into analyst estimates and revision trends for any stock using Yahoo Finance data. Use when the user wants to understand analyst estimate direction, how EPS or revenue forecasts changed over time, compare estimate distributions, or analyze growth projections across periods. Triggers: "estimate analysis for AAPL", "analyst estimate trends for NVDA", "EPS revisions for TSLA", "how have estimates changed for MSFT", "estimate revisions", "EPS trend", "revenue estimates", "consensus changes", "analyst estimates", "estimate distribution", "growth estimates for", "estimate momentum", "revision trend", "forward estimates", "next quarter estimates", "annual estimates", "estimate spread", "bull vs bear estimates", "estimate range", or any request about tracking or comparing analyst estimates/revisions. Use this skill when the user asks about estimates beyond a simple lookup — if they want context, trends, or analysis, this is the right skill.

72

Quality

89%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

78%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, actionable skill body with clear sequencing and good progressive disclosure to one reference file. The main gaps are moderate verbosity from illustrative example tables and analysis-computation logic left as prose in the body rather than executable code.

Suggestions

Replace the five illustrative output tables with a single compact example plus a note on expected columns, to cut tokens without losing format guidance.

Add an explicit validation checkpoint after Step 2 (e.g., check each estimate DataFrame is non-empty and warn on missing coverage) before routing in Step 3.

Move the revision-ratio and range-width calculations from prose into a short executable snippet in the body, mirroring the code already in the reference.

DimensionReasoningScore

Conciseness

Mostly efficient and free of generic-concept padding, but the five fully-populated example tables of illustrative numbers plus the interpretive bullets add length that could be trimmed without losing clarity.

4 / 5

Actionability

Provides executable data-fetching code in Step 2 and install code in Step 1, but the Step 4 analysis computations (range-width %, revision ratio, beat rate) are described in prose rather than as executable code in the body, with the full code deferred to the reference file.

4 / 5

Workflow Clarity

A clear five-step sequence (install → fetch → route → build → synthesize) with a routing table and an install-state check, but the main flow lacks an explicit 'verify fetched data is non-empty' checkpoint before analysis, which the reference only covers separately.

4 / 5

Progressive Disclosure

Well-organized overview with a single clearly-signaled one-level-deep reference (references/api_reference.md) for the bulk API detail, and the body keeps to getting-started structure and expected output format.

5 / 5

Total

17

/

20

Passed

Description

100%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, third-person description that concretely names the capability, gives explicit 'Use when' guidance, and supplies a rich set of natural trigger phrases with a clear boundary against simple lookups. Its only weakness is verbosity: the trigger list is long enough that it slightly over-pads the field, though the rubric rewards trigger coverage.

DimensionReasoningScore

Specificity

Lists multiple concrete analysis actions — 'understand analyst estimate direction', 'how EPS or revenue forecasts changed over time', 'compare estimate distributions', 'analyze growth projections across periods' — giving comprehensive coverage rather than a single generic verb.

5 / 5

Completeness

Explicitly states both what it does ('Deep-dive into analyst estimates and revision trends ... using Yahoo Finance data') and when to use it ('Use when the user wants to ...'), reinforced with concrete trigger phrases and a boundary clause ('beyond a simple lookup').

5 / 5

Trigger Term Quality

Provides extensive natural-language triggers users would actually say ('EPS revisions for TSLA', 'how have estimates changed for MSFT', 'estimate momentum', 'bull vs bear estimates') plus synonyms and phrasings, matching the comprehensive-coverage anchor.

5 / 5

Distinctiveness Conflict Risk

The analyst-estimates/revisions niche is specific and the triggers (EPS trend, revision momentum, estimate spread) are distinct from general stock-analysis skills, keeping conflict risk minimal.

5 / 5

Total

20

/

20

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
himself65/finance-skills
Reviewed

Table of Contents

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