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.

Quality

77%

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tessl review fix ./skills/weekly-performance-digest/SKILL.md

Quality

Content

80%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 a copy-paste-ready command and clean progressive disclosure to real reference/script files. The main gap is the absence of an explicit validation/verification step in the batch digest workflow, which caps workflow clarity at 3.

Suggestions

Add an explicit verification step after running the script: check the exit code is 0, confirm total_trades is plausible for the date range, and verify the JSON parses before consuming it downstream.

Add a feedback loop for the batch operation: if the report shows zero trades or anomalous metrics, check the --from-date/--to-date range and thesis status==CLOSED, then re-run.

Dimension	Reasoning	Score
Conciseness	The body is efficient and assumes Claude's competence (it uses "win rate", "MAE/MFE", "R-multiple" without explaining them), but the full JSON output example with several empty pattern sub-objects ("by_exit_reason": {}, "by_thesis_type": {}, ...) is slightly heavy and could be trimmed.	4 / 5
Actionability	Step 1 provides a copy-paste-ready command with real flags and documented defaults ("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"), the script file exists, and output filenames are concrete — fully executable covering the common case.	5 / 5
Workflow Clarity	A clear 3-step sequence exists (run digest → read report → feed downstream), but this batch operation over all closed theses has no explicit validation/verification checkpoint (no exit-code check, no plausibility check of total_trades, no validate→fix→retry loop), so per the batch-operation guideline workflow clarity is capped at 3.	3 / 5
Progressive Disclosure	A clear overview in SKILL.md points to one-level-deep, well-signaled bundle files in the Resources section — "scripts/generate_weekly_digest.py — digest generator" and "references/weekly-digest-metrics.md — metric formulas and interpretation" — both of which exist, with detailed material appropriately split out and easy to navigate.	5 / 5
	Total	17 / 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 specific, well-niched description that clearly states what it does and the metrics it computes, but it lacks an explicit "Use when..." trigger clause, capping completeness at 3. Trigger term coverage is good but could add natural synonyms.

Suggestions

Add an explicit "Use when..." clause, e.g. "Use at the end of a trading week to review realized performance, or when preparing a month-end review from weekly digests."

Broaden trigger terms with natural synonyms users would say, such as "weekly trading review", "trade review", or "realized P&L review".

Dimension	Reasoning	Score
Specificity	"Generate a weekly performance summary" plus an enumerated list of concrete computed outputs — "win rate, expectancy, profit factor, R-multiple, MAE/MFE, and win/loss pattern analysis by source skill, exit reason, thesis type, sector, and mechanism" — gives comprehensive, specific coverage of capabilities with no gaps.	5 / 5
Completeness	The "what" is explicit ("Generate a weekly performance summary from closed trader-memory-core theses") but there is no "Use when..." clause or equivalent explicit trigger guidance, so per the judging guideline completeness is capped at 3 with "when" only weakly implied by "weekly".	3 / 5
Trigger Term Quality	Natural domain phrases are present ("weekly performance summary", "win rate", "expectancy", "pattern analysis"), but common synonyms a user might say like "weekly trading review", "trade review", or "realized P&L review" are missing, so it is good but not comprehensive.	4 / 5
Distinctiveness Conflict Risk	It is tied to a clear niche — "closed trader-memory-core theses" with specific trading metrics and pattern dimensions — giving distinct triggers and minimal conflict risk with other skills.	5 / 5
	Total	17 / 20 Passed

Validation

100%

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: tradermonty/claude-trading-skills
Path: skills/weekly-performance-digest/SKILL.md
Commit: 51c7907

Reviewed: ~7 hours ago

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