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weekly-performance-digest

Generate a weekly performance summary from closed trader-memory-core theses — win rate, expectancy, profit factor, R-multiple, MAE/MFE, and win/loss pattern analysis by source skill, exit reason, thesis type, sector, and mechanism. No API required; pure local calculation.

67

Quality

84%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

86%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-crafted skill body: executable commands with documented defaults, a complete output contract, and clean separation of metric definitions into a real, one-level-deep reference file. The only notable improvements are de-duplicating the double-counting explanation and adding a lightweight verification step after the digest run.

DimensionReasoningScore

Conciseness

The body is dense and assumes competence — no padding, no explanation of concepts Claude already knows, and the JSON example documents the output contract rather than over-teaching. It is not a 5 because the double-counting invariant is explained twice at length ("How It Works" bullet and "Key Principles" 1–2), and "Pure calculation — no API key required" repeats the description. It is not a 3 because these are minor trims, not whole unnecessary sections.

4 / 5

Actionability

Step 1 gives a fully executable, copy-paste-ready command with realistic flags ("python3 skills/weekly-performance-digest/scripts/generate_weekly_digest.py --state-dir state/theses --from-date 2026-06-13 --to-date 2026-06-20 --output-dir reports/ -v"), documents all defaults, names the exact output files, and shows the complete JSON output schema. Coverage of the common case (default trailing-7-day run) is explicit.

5 / 5

Workflow Clarity

A clear three-step sequence (run → read report → optional downstream) with concrete commands, flag defaults, and explicit edge-case behavior ("An empty week still produces a valid report with zeroed metrics (exit code 0)"). It is not a 5 because there is no explicit validation/checkpoint step (e.g., confirming the output files were written or inspecting summary counts before interpreting), though as a read-only descriptive skill it carries little risk; it is not a 3 because the sequence is complete and unambiguous with implicit checkpoints.

4 / 5

Progressive Disclosure

The body is a well-organized overview that moves detail to one-level-deep, verified bundle files: "scripts/generate_weekly_digest.py — digest generator (JSON + Markdown)" and "references/weekly-digest-metrics.md — metric formulas and interpretation", both of which exist in the bundle and match their descriptions. Inline content (workflow, output schema, core invariants) is appropriately kept in SKILL.md, and navigation via the Resources section is clear.

5 / 5

Total

18

/

20

Passed

Description

75%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 highly specific, third-person description that comprehensively enumerates the skill's capabilities and is clearly distinguishable from neighboring skills. Its main weakness is the complete absence of a "Use when..." trigger clause, which both caps completeness and leaves natural activation phrases (weekly review, trade journal, P&L review) implicit.

Suggestions

Append an explicit trigger clause such as "Use at the end of a trading week to review closed-trade performance, or when the user asks for a weekly/periodic trading review or win-rate/P&L summary."

Add one or two natural synonyms users would say (e.g., "trading review", "trade performance", "P&L") to broaden trigger-term coverage.

Optionally state when NOT to use it (single-trade review vs. aggregate review) in the description to further reduce conflict with sibling skills.

DimensionReasoningScore

Specificity

"Generate a weekly performance summary from closed trader-memory-core theses — win rate, expectancy, profit factor, R-multiple, MAE/MFE, and win/loss pattern analysis by source skill, exit reason, thesis type, sector, and mechanism" lists multiple specific concrete capabilities with comprehensive coverage of the digest's metric and breakdown dimensions. It is not a 4 because coverage is thorough rather than having minor gaps, and it uses proper third-person voice ("Generate").

5 / 5

Completeness

The "what" is clearly and concretely answered (metrics, breakdown dimensions, local calculation), but there is no "Use when..." clause or equivalent explicit trigger guidance, which caps completeness at 3 per the judging guidelines. It is not a 2 because the "what" is fully explicit rather than vague; it is not a 4 because no temporal or situational usage trigger is stated at all.

3 / 5

Trigger Term Quality

Good natural keyword coverage — "weekly performance summary", "win rate", "expectancy", "profit factor", "closed" trades, "trader-memory-core" — phrases a user reviewing trading performance would plausibly say. It falls short of 5 because common synonyms and variations like "trading review", "trade journal", "P&L review", or "postmortem" are absent, leaving a few natural entry points uncovered.

4 / 5

Distinctiveness Conflict Risk

"from closed trader-memory-core theses" plus the distinctive metric set (R-multiple, MAE/MFE, pattern analysis by exit reason and mechanism) carves out a clear niche with minimal overlap risk against generic reporting or single-trade review skills. It is not a 4 because the domain anchoring and unique metric vocabulary make confusion with any neighboring skill unlikely.

5 / 5

Total

17

/

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
tradermonty/claude-trading-skills
Reviewed

Table of Contents

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