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santa-method

Multi-agent adversarial verification with convergence loop. Two independent review agents must both pass before output ships.

Quality

69%

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tessl review fix ./skills/santa-method/SKILL.md

The canonical home for this skill is santa-method in affaan-m/ECC

SKILL.md
Quality
Evals
Security

Quality

Content

66%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 methodology skill with an exemplary workflow: clearly sequenced phases, a hard verdict gate, a bounded fix loop with fresh reviewers, and escalation. The weaknesses are pseudocode presented as Python where the reviewer prompt is the only truly executable artifact, and redundancy across the architecture diagram, phase details, and Pattern A.

Suggestions

Either make the Python examples executable (define `dedupe`, `santa_full`, `fix_agent`, `ship`) or explicitly label them as pseudocode/templates, per the rubric guideline on pseudocode justification.

Trim redundancy: collapse Pattern A's duplicated Agent invocation into Phase 2 (or vice versa) and tighten the Cost Analysis section, which currently reads as persuasion rather than instruction.

Move the domain-specific rubric extensions, Integration, Metrics, and Cost Analysis tables into reference files (e.g. references/rubric-extensions.md) so the core four-phase method stays lean in SKILL.md.

DimensionReasoningScore

Conciseness

The body is mostly efficient — the core insight paragraph, phase details, and failure-mode table each earn their place — but there is redundant overlap: the ASCII architecture diagram restates the phase details, and Pattern A's Agent invocation repeats Phase 2's spawning guidance with a divergent, simpler prompt. The Cost Analysis section also drifts into padded rhetoric ('reputation damage', 'trust erosion') rather than instruction. Not a 2 because no section teaches concepts Claude already knows; not a 4 because the repetition between Architecture, Phase 2, and Pattern A is real trimming material.

3 / 5

Actionability

The REVIEWER_PROMPT template is genuinely copy-paste ready and the rubric tables give objective pass conditions, but the surrounding ```python blocks are pseudocode — `santa_verdict` references undefined `dedupe`, `santa_batch` calls undefined `santa_full`, `fix_agent`, `ship`, and `escalate_to_human`, and the Agent(...) calls are illustrative. The rubric explicitly penalizes pseudocode not justified as such, matching anchor 3 ('pseudocode instead of executable code'); the complete prompt template keeps it from scoring lower.

3 / 5

Workflow Clarity

The four phases are explicitly sequenced (generate → dual review → verdict gate → fix loop) with a hard validation checkpoint (both reviewers must PASS), an explicit feedback loop (fix all flagged issues, re-run fresh reviewers), bounded iterations (MAX_ITERATIONS = 3), and a defined escalation path. This matches the anchor-5 pattern of clear sequence, explicit validation steps, feedback loops for error recovery, and process checklists (the failure-modes and invariants tables).

5 / 5

Progressive Disclosure

The single-file body has a clear overview (When to Activate, Architecture) with well-labeled sections, and no bundle files exist to reference. It is not a 5 because at 300+ lines, secondary material such as the domain-specific rubric extension tables, the Integration with Other Skills table, Metrics, and Cost Analysis is inline where a references/ split would keep the core method lean; it is not a 3 because the structure that is present is well-signaled and easy to navigate.

4 / 5

Total

15

/

20

Passed

Description

58%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 clear, mechanism-specific description that communicates the what concretely and distinctively. Its main weakness is the complete absence of when-to-use trigger guidance, which both caps completeness and leaves natural trigger terms underrepresented.

Suggestions

Add an explicit 'Use when...' clause, e.g. 'Use when output will be published or deployed without human review, when accuracy/compliance must be verified, or when hallucination risk is elevated.'

Include natural user phrasings as trigger terms, such as 'double-check', 'QA', 'quality gate', or 'verify before shipping/deploying'.

Briefly name the full loop (review → fix → re-review until both pass, with escalation) so the convergence and fix-cycle behavior is discoverable from the description alone.

DimensionReasoningScore

Specificity

The description lists several concrete behaviors — "Multi-agent adversarial verification", "convergence loop", "Two independent review agents must both pass before output ships" — which function as specific actions rather than vague domain-naming. It falls short of a 5 because it does not enumerate the fuller pipeline (fix cycle, escalation, batch sampling) that the body actually covers.

4 / 5

Completeness

The "what" is clearly stated (adversarial dual-agent verification with a both-must-pass gate), but there is no "Use when..." clause or any equivalent explicit trigger guidance, which caps completeness at 3 per the judging guidelines. It cannot score 4 without at least a weak explicit 'when'.

3 / 5

Trigger Term Quality

Terms like "verification", "review agents", and "output ships" are relevant, but the description misses common natural phrasings users would actually say such as "double-check", "QA", "quality check", or "verify before publishing/deploying". Not a 2 because the present keywords are meaningful rather than generic filler; not a 4 because several obvious user synonyms are absent.

3 / 5

Distinctiveness Conflict Risk

The dual-reviewer convergence-gate niche is fairly distinct with specific triggers like "must both pass"; only minor overlap risk with general code-review or eval skills. It is not a 5 because "multi-agent verification" alone could plausibly collide with other review/QA skills.

4 / 5

Total

14

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

valeriibeck-star/claude-skills

Path

skills/santa-method/SKILL.md

Reviewed

Table of Contents

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