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launch-monitor

Use when the user asks to "monitor my launch", "track our Product Hunt / Hacker News ranking", or "watch the launch window"; runs the T-0 to T+30 window watch — pre-launch instrumentation verification (UTM/event checks, the upstream of RAMP P1), HN rank/points/comments polling with a comments-over-points flamewar early-warning (Estimated heuristic), PH votes/featured status, store charts and reviews, news echo, D0/W1/M1 KPI snapshots vs targets, spike-vs-sustain and owned-capture reads, and alert thresholds against the launch-tier KPI targets. Not for launch-day go/rollback calls — use launch-day-conductor; not for metric deep-dives — use performance-analyzer; not for SEO rank tracking — use rank-tracker. 发布监控/排名轮询/火焰战比/spike-sustain

65

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

62%Weight 40%Scale 1-3

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, scope-disciplined runbook with a clear sequenced workflow and explicit verification/routing checkpoints. Its weak spots are conciseness (redundant scope-guard restatements and internal jargon), lack of any executable examples, and references to bundle files that are not present in the actual bundle.

Suggestions

Collapse the repeated scope-guard / negative-scope list into the single Scope guard section and have the Instructions and Next Best Skill sections reference it, to remove the triple restatement and tighten conciseness.

Add at least one concrete connector invocation example (e.g. a sample command or expected output shape for scripts/connectors/hn.py) so the actionability reaches copy-paste-ready guidance.

Either include the referenced bundle files (references/ramp-benchmark.md, CONNECTORS.md, SECURITY.md, scripts/connectors/*.py) in the bundle or remove the dangling path references, and factor the inlined connector list into a single Data Sources section.

DimensionReasoningScore

Conciseness

Largely earns its tokens with no concept-explaining preamble, but carries redundancy — the scope guard / negative-scope list is restated across Scope guard, Instructions, and Next Best Skill, and RAMP sub-item mapping is repeated — fitting the 'mostly efficient but could be tightened' anchor rather than the fully lean one.

2 / 3

Actionability

Names concrete artifacts and rules (connectors like 'scripts/connectors/gdelt.py' with '>=5s between calls', labeling 'Measured / User-provided / Estimated', write paths via 'operation: propose'), but provides no executable code or command samples inline, keeping it at 'some concrete guidance but incomplete' rather than copy-paste ready.

2 / 3

Workflow Clarity

The 8-step Instructions form a clear sequence with explicit checkpoints and routing rules — 'an unverifiable surface is a named blocker... not a silent pass', 'Done when instrumentation is verified per surface before T-0' — and the monitoring ops are non-destructive, matching the 'clear sequence with explicit validation steps' anchor.

3 / 3

Progressive Disclosure

Sections are well-organized and reference files one level deep with descriptive labels, but the bundle contains no references/, scripts/, or assets/ directories while the body repeatedly cites 'scripts/connectors/*.py', '../../../references/ramp-benchmark.md', '../../../CONNECTORS.md' and other paths that cannot be verified, plus the connector list is inlined three times — fitting 'some structure but could be better organized'.

2 / 3

Total

9

/

12

Passed

Description

100%Weight 40%Scale 1-3

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 strong: it states concrete capabilities, gives natural trigger phrasings, answers both what and when, and negative-scopes against sibling skills. Minor token noise from internal jargon ('RAMP P1', 'spike-sustain') and the trailing Chinese keywords does not materially weaken any dimension.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'pre-launch instrumentation verification (UTM/event checks)', 'HN rank/points/comments polling with a comments-over-points flamewar early-warning', 'PH votes/featured status, store charts and reviews, news echo, D0/W1/M1 KPI snapshots vs targets, spike-vs-sustain and owned-capture reads' — matching the 'multiple specific concrete actions' anchor.

3 / 3

Completeness

Explicitly answers both 'what' (the telemetry watch actions) and 'when' via a 'Use when the user asks to...' clause with concrete triggers, matching the 'clearly answers both what AND when with explicit triggers' anchor.

3 / 3

Trigger Term Quality

Quotes natural phrasings a user would actually say — 'monitor my launch', 'track our Product Hunt / Hacker News ranking', 'watch the launch window' — giving good coverage of natural trigger terms.

3 / 3

Distinctiveness Conflict Risk

Clear niche (launch-window telemetry watch) reinforced by explicit negative scoping — 'Not for launch-day go/rollback calls — use launch-day-conductor; not for metric deep-dives — use performance-analyzer; not for SEO rank tracking — use rank-tracker' — making conflict unlikely.

3 / 3

Total

12

/

12

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: 35 suspicious

Warning

referenced_paths_exist

Referenced path issues: 15 missing, 15 deeper-than-1-level

Warning

Total

12

/

16

Passed

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

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