SKILLEMALL.ai
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BF astro-lunar-insights

Lunar phase analysis and Moon influence on a person using Swiss Ephemeris (pyswisseph). Calculates Moon phases (exact dates), transit Moon aspects to natal Moon (personal lunar cycle), transit Moon through natal houses, personal solar-lunar phase (Moon -> Natal Sun), lunar day number (tithi), Moon speed, illumination, perigee/apogee, and transit Moon aspects to all natal planets. Bilingual (RU/EN). Renders a 2-wheel chart (Moon phase wheel + natal wheel with transit Moon) with 3-group legend, text panel, and QR code for donations. Windows 10/11 compatible. Accuracy ensured by Swiss Ephemeris (JPL DE431 ephemerides, ~0.003° precision). Requires: Python 3.14.x, Pillow 12.x, MSVC++ Redist 2015–2022. Related: astro-daily-transits skill for daily transit forecast, astro-natal-chart skill for natal chart calculation.

ClawHub Agent Skills author: dynamicsAlex v1.3.3 MIT-0 7 files body ≈ 5 628 tokens Open the sourceclawhub.ai↗ analyzed 28 h ago

Lunar phase analysis and Moon influence on a person using Swiss Ephemeris (pyswisseph).

As a process F 38/100 · Will not run — References files that are not bundled: scripts/swisseph.cp314-win_amd64.pyd.dat, scripts/seguisym.ttf.dat, scripts/segoeuisl.ttf.dat

AnalyzerSoftware developmentAI and agentsData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
76/100
safety, quality, tests
Safety 60%
100
Quality 40%
39
Run on models
none yet
Process rating
F
38/100
Will not run
References files that are not bundled: scripts/swisseph.cp314-win_amd64.pyd.dat, scripts/seguisym.ttf.dat, scripts/segoeuisl.ttf.dat
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 3, column 14: description: Lunar phase analysis and Moon influence on a person using Swiss Ep… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5628 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: scripts/swisseph.cp314-win_amd64.pyd.dat
  • warning missing-ref reference to a missing file: scripts/seguisym.ttf.dat
  • warning missing-ref reference to a missing file: scripts/segoeuisl.ttf.dat

Process rating: all ten parameters 38/100

Will not run. References files that are not bundled: scripts/swisseph.cp314-win_amd64.pyd.dat, scripts/seguisym.ttf.dat, scripts/segoeuisl.ttf.dat
  • 0Tools and files. 3 referenced file(s) missing: scripts/swisseph.cp314-win_amd64.pyd.dat, scripts/seguisym.ttf.dat, scripts/segoeuisl.ttf.dat
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Steps. 90 steps, 6 vague phrases
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 5628 tokens
  • 100Consistency. Name and required fields are in place
  • low 14 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 822: 120–800 characters recommended
  • -31 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +4Structure: 35 headings
  • +3Step-by-step instructions: 90 items
  • +3Output format is stated explicitly
  • +4Has examples (9 code blocks)
  • +2Bilingual instructions (RU + EN)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 39.

External checks

ClawHub: suspicious
The skill appears to perform the advertised lunar-chart analysis, but it should be reviewed because it silently installs a package and runs a bundled Windows binary renamed as a data file.
LLM: suspicious (medium) · VirusTotal: · 24 Jun 2026