screen

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更新日2026年7月7日 21:21

Screen a Target against the hard gates (the screen verb). Applies auto — the write IS the screen.

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Play-New/bending-spoons-ontology

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関連職種SOC

SOC 職業分類に基づく

財務・投資アナリストビジネス・金融業務職·SOC 13-2051

SKILL.md

readonly

name	screen
description	Screen a Target against the hard gates (the screen verb). Applies auto — the write IS the screen.
disable-model-invocation	true

Execute the screen verb of the Bending Spoons world model, per its contract.

Read the contract: capabilities/actions/screen-target.md — parameters, submission criteria, gate. Follow it exactly.
ESTIMATE THE GATES with the radar's structured tiers before asking the user anything:
- US-listed candidate → python3 .claude/skills/radar-sweep/scripts/radar_sweep.py "TKR" --gates (revenue band · HQ · sector, [derived] from EDGAR)
- EU-listed / unknown → ... "Legal Name" --company (GLEIF → ESEF chain; honest n.d. for privates)
- private → the press recipes in the radar-sweep skill (triangulate ≥2 sources; everything [to-validate — press only]) + --loyalty "Brand" as the predictable-earnings proxy (rating base · interest trend · community) Fill the nine gate values from these, marked by provenance; ask the user only for what remains.
Propose (phase 1 — writes nothing): python3 -c "import sys; sys.path.insert(0,'mcp'); import engine, json; print(json.dumps(engine.propose('screen', PARAMS), indent=2))" If the engine REFUSES, report the refusal verbatim — it is a submission criterion firing (a will constraint or an invariant), not an error to work around.
Show the user: the checks, the gate, and the exact diff. screen applies auto (no approver needed): the write is the screen itself; admission to underwriting stays human.
Only on the user's explicit yes, apply (phase 2): python3 -c "import sys; sys.path.insert(0,'mcp'); import engine; print(engine.apply('PROPOSAL_ID', 'USER_NAME'))" The engine runs the audit and commits if green; report the outcome. Never edit the csvs directly.

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Create a new Target in the pipeline (the source verb). Human-gated: admission needs the user's approval.

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name	screen
description	Screen a Target against the hard gates (the screen verb). Applies auto — the write IS the screen.
disable-model-invocation	true

Execute the screen verb of the Bending Spoons world model, per its contract.

Read the contract: capabilities/actions/screen-target.md — parameters, submission criteria, gate. Follow it exactly.
ESTIMATE THE GATES with the radar's structured tiers before asking the user anything:
- US-listed candidate → python3 .claude/skills/radar-sweep/scripts/radar_sweep.py "TKR" --gates (revenue band · HQ · sector, [derived] from EDGAR)
- EU-listed / unknown → ... "Legal Name" --company (GLEIF → ESEF chain; honest n.d. for privates)
- private → the press recipes in the radar-sweep skill (triangulate ≥2 sources; everything [to-validate — press only]) + --loyalty "Brand" as the predictable-earnings proxy (rating base · interest trend · community) Fill the nine gate values from these, marked by provenance; ask the user only for what remains.
Propose (phase 1 — writes nothing): python3 -c "import sys; sys.path.insert(0,'mcp'); import engine, json; print(json.dumps(engine.propose('screen', PARAMS), indent=2))" If the engine REFUSES, report the refusal verbatim — it is a submission criterion firing (a will constraint or an invariant), not an error to work around.
Show the user: the checks, the gate, and the exact diff. screen applies auto (no approver needed): the write is the screen itself; admission to underwriting stays human.
Only on the user's explicit yes, apply (phase 2): python3 -c "import sys; sys.path.insert(0,'mcp'); import engine; print(engine.apply('PROPOSAL_ID', 'USER_NAME'))" The engine runs the audit and commits if green; report the outcome. Never edit the csvs directly.