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python-math

Small Python utilities for math and text files.

Quality

62%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./examples/skillrun/skills/python_math/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

82%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 is an exemplary lean, executable skill document: two copy-paste-ready commands, a real referenced script, and no wasted tokens. The only gaps are minor — unstated output-directory prerequisite, an unexplained "returned as text" mechanism, and plain-text rather than markdown section headers.

Suggestions

Note that the `out/` directory must be created before redirecting (e.g., `mkdir -p out`), or have the script create it, to keep the examples copy-paste runnable.

Either explain concretely how results are "returned as text" or drop that phrase, and use markdown headers (## Overview, ## Examples) for scannability.

DimensionReasoningScore

Conciseness

The body is ~30 lean lines with zero padding and no explanation of concepts Claude already knows; every section (Overview, Examples, Output Files) earns its place. This matches anchor 5 ("Lean and efficient; assumes Claude's competence; every token earns its place").

5 / 5

Actionability

Both examples are concrete, copy-paste-ready commands (`python3 scripts/fib.py 10 > out/fib.txt` and the stdin-summing heredoc), and scripts/fib.py is a real bundle file. It falls short of anchor 5 because coverage of "common cases" is thin (only two examples for a skill claiming math and text utilities) and minor details are missing, e.g., that the `out/` directory must exist before redirecting output.

4 / 5

Workflow Clarity

As a simple single-action skill, running each example is unambiguous, which supports a high score; however, the overview states "Results can be returned as text and saved as output files" without ever instructing how results are returned, and the Output Files section lists only one file. This places it at anchor 4 ("Clear sequence with most checkpoints present; minor validation gaps") rather than 5.

4 / 5

Progressive Disclosure

The skill is under 50 lines with no need for external references, and its one bundle path (`scripts/fib.py`) is real and clearly signaled one level deep, so structure is appropriate. It misses anchor 5 only on organization polish: section labels ("Overview", "Examples", "Output Files") are plain text rather than markdown headers, making the structure slightly less scannable.

4 / 5

Total

17

/

20

Passed

Description

25%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 names a domain but provides no concrete actions, no trigger guidance, and no "when to use" clause, making it vague and highly conflict-prone with other Python or text-handling skills. It reads like the "bad_overall_examples" ("Processes data") more than any good example. It needs concrete capability verbs and an explicit "Use when..." trigger clause.

Suggestions

Replace "utilities" with concrete action verbs, e.g., "Runs short Python scripts to compute math sequences (Fibonacci), sum integer lists, and process text files."

Add an explicit trigger clause, e.g., "Use when the user asks to calculate values, generate number sequences, or run quick Python computations on text."

Include natural trigger terms and synonyms users would actually say ("fibonacci", "sum", "calculate", "python script") to reduce overlap with generic Python/text skills and improve distinctiveness.

DimensionReasoningScore

Specificity

"Small Python utilities for math and text files" names the domain (Python, math, text files) but "utilities" names no concrete action, matching anchor 2 ("Names the domain but actions are minimal or generic"). It does not reach anchor 3 because no concrete action verbs (e.g., computes, sums, parses) are listed.

2 / 5

Completeness

The description has only a vague "what" ("small Python utilities") and contains no "when" / "Use when..." clause at all — an exact match for anchor 2 ("Has a vague 'what' and no 'when'"). It cannot score 3 because the "what" lists no clear concrete actions.

2 / 5

Trigger Term Quality

The only keywords are the generic "Python", "math", and "text files"; natural phrases a user would actually say ("calculate", "sum numbers", "fibonacci", "parse a text file") and file extensions are missing. This fits anchor 2 ("One or two generic keywords; missing the natural phrases users say") better than anchor 3, which expects at least some specific relevant keywords like "PDF" in the anchor example.

2 / 5

Distinctiveness Conflict Risk

"Python utilities for math and text files" is very broad and would overlap with virtually any Python, math, or text-processing skill, matching anchor 2 ("Very broad; high overlap risk with many similar skills"). It is not entirely generic enough for anchor 1, since it does constrain the domain to Python math/text utilities.

2 / 5

Total

8

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

trpc-group/trpc-agent-go

Path

examples/skillrun/skills/python_math/SKILL.md

Reviewed

Table of Contents

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