screen

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Aktualisiert7. Juli 2026 um 21:21

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

Installation

Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.

Quelle

Play-New

Play-New/bending-spoons-ontology

GitHub-Repository öffnen Creator-Repositorys ansehen

Download

Verwandte BerufeSOC

Basierend auf der SOC-Berufsklassifikation

Finanz- und InvestitionsanalystenWirtschafts- und Finanzberufe·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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Run the model's audit (the model's audit service, mechanical subset) and summarize — green/red, defects with the invariant each violates. Run after any batch of edits.

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Close an acquisition: create the Deal + Business + Interface(s) (GATE 2: go/no-go is the user's).

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The desk over the whole deal machine — pipeline status, pending proposals, and which verb applies next. Start here ("/deal-desk") to see the state and be guided to the right action skill.

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hire

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The hiring assistant — run a candidate through Bending Spoons' selection funnel and score them against the disclosed gates. Read-only, advisory: it drafts a recommendation; the committee decides. The people-side twin of screen-target.

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source

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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.