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positioning-truth-tracer

Use when the user asks to "check our positioning against what we can actually ship", "trace which differentiators we can defend", or "reconcile the positioning canvas with the claims ledger"; reconciles the reused positioning canvas against the shippable stage and the claims ledger to produce a differentiation truth set — every differentiating claim verifiable or marked '[needs source]' — that TALE-T1 is judged against. Not for building the canvas — use positioning-mapper; not for adjudicating claims — use offer-claims-registry; not for authoring the message house — use message-system-architect. 定位真相/差异化校准/可交付现实/主张核对

66

Quality

82%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

77%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 a well-structured, actionable Trace-phase workflow with strong sequencing, validation gates, and a clean reference layer. Its main weakness is repetitive routing/propose-boilerplate that inflates the token budget without adding information.

Suggestions

Define the 'authorized operation: propose request to registry-events.py' write pattern once in the Skill Contract, then reference it by name in Instructions and Save Results instead of repeating the full phrase ~6 times.

Consolidate the upstream/downstream routing (positioning-mapper, message-system-architect, offer-claims-registry) into one place — either Scope guard or Next Best Skill — rather than restating the same boundaries across four sections.

Inline a compact example of the differentiation truth set output shape instead of deferring entirely to skill-contract.md §Handoff Summary, so the primary deliverable is copy-paste ready.

DimensionReasoningScore

Conciseness

The body is mostly efficient and assumes Claude's competence (no concept explanations), but the phrase 'via an authorized operation: propose request to registry-events.py' is repeated verbatim ~6 times and the upstream/downstream routing boundaries are restated across Scope guard, Data Sources, Reference Materials, and Next Best Skill, which could be tightened.

3 / 5

Actionability

Concrete, specific guidance throughout — exact memory paths (memory/launch-registry/, memory/claims/claims-ledger.md, memory/narrative/positioning-truth-tracer/), the onlyness template '[Product] is the only [category frame] that [defensible value] for [beachhead]', and explicit decision rules — held back from a 5 only because the output format defers to an external reference rather than giving a copy-paste example.

4 / 5

Workflow Clarity

A clear 7-step sequence with explicit validation checkpoints (confirm canvas exists or stop with NEEDS_INPUT; pull stage or ask), feedback loops (step 5 failure recovery: sharpen the value rather than soften wording), a 'Done when' checklist, and a propose-only/ask-before-writing gate that validates every memory write.

5 / 5

Progressive Disclosure

The body is an overview with a dedicated Reference Materials section listing nine one-level-deep, clearly labeled references (stimulus-binding.md, tale-benchmark.md, skill-contract.md, CONNECTORS.md, SECURITY.md, plus sibling SKILL.md links); no bundle files exist to verify, and navigation is easy.

5 / 5

Total

17

/

20

Passed

Description

87%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 is well-crafted: it pairs concrete trigger phrases with a clear statement of what the skill produces, and uses explicit 'Not for...' routing to stay distinct from sibling skills. Its only weakness is domain-specific jargon that slightly limits natural-term breadth.

DimensionReasoningScore

Specificity

Lists several concrete actions — 'reconciles the reused positioning canvas against the shippable stage and the claims ledger to produce a differentiation truth set', marking every claim 'verifiable or marked [needs source]' — with comprehensive coverage of the skill's job, held back from a 5 only by niche jargon that narrows the action list.

4 / 5

Completeness

Explicitly answers both 'what' (reconciles canvas against stage and ledger to produce a differentiation truth set) and 'when' (a leading 'Use when the user asks to...' clause with concrete trigger phrases), plus explicit 'Not for...' boundary guidance.

5 / 5

Trigger Term Quality

Quotes three natural trigger phrases a user would say — 'check our positioning against what we can actually ship', 'trace which differentiators we can defend', 'reconcile the positioning canvas with the claims ledger' — giving good keyword coverage, though a few common synonyms are missing.

4 / 5

Distinctiveness Conflict Risk

Carves a clear niche — positioning-truth tracing — and explicitly routes away from positioning-mapper, offer-claims-registry, and message-system-architect, minimizing the chance of triggering for the wrong skill.

5 / 5

Total

18

/

20

Passed

Validation

75%

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

Validation12 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

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

Warning

relative_links

Relative link issues: 32 suspicious

Warning

referenced_paths_exist

Referenced path issues: 2 missing, 2 deeper-than-1-level

Warning

Total

12

/

16

Passed

Repository
aaron-he-zhu/aaron-marketing-skills
Reviewed

Table of Contents

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