القائمة
Use when deciding whether a research claim should enter the optional Lean formalization lane.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | lean-formalization-intake |
| description | Use when deciding whether a research claim should enter the optional Lean formalization lane. |
On native Windows, use the managed Windows runner and the native runtime command target. Set $runtime to the installed runtime root. Multi-agent installs usually use %LOCALAPPDATA%\ai-agents-skills\runtime. Then run:
$runtime = if ($env:AAS_RUNTIME_ROOT) { $env:AAS_RUNTIME_ROOT } else { "$env:LOCALAPPDATA\ai-agents-skills\runtime" }
& "$runtime\run_skill.bat" "skills/lean-formalization-intake/run_lean_formalization_intake.bat" doctor
PowerShell runner target:
& "$runtime\run_skill.ps1" "skills/lean-formalization-intake/run_lean_formalization_intake.ps1" doctor
POSIX examples below use run_skill.sh and .sh command targets; use the Windows command target above on native Windows.
Use this skill before spending effort on Lean formalization. It decides whether a research claim is suitable for the optional formal lane and records a conservative decision:
proceed: definitions and scope look suitable enough to try formalizationdefer: formalization is relevant but blocked by definitions, toolchain, library support, semantic alignment, or budgetnot_applicable: Lean is not useful for this claim or outside scopeblocked: formal support was required but cannot proceed without clarification or missing toolingdefer, not_applicable, and missing Lean are not failed theorem evidence. They are only formal-lane status.
Check the local tool status:
bash "$AAS_RUNTIME_ROOT/run_skill.sh" \
skills/lean-formalization-intake/run_lean_formalization_intake.sh doctor
Run non-installing version/toolchain probes when you need reproducibility metadata:
bash "$AAS_RUNTIME_ROOT/run_skill.sh" \
skills/lean-formalization-intake/run_lean_formalization_intake.sh doctor --probe
Assess a claim:
bash "$AAS_RUNTIME_ROOT/run_skill.sh" \
skills/lean-formalization-intake/run_lean_formalization_intake.sh assess \
--claim "Every finite tree has a leaf" \
--claim-id C1 \
--output formal/intake-C1.json
Set AAS_LEAN or AAS_LAKE to select a specific already-installed local
executable. Invalid explicit paths are reported as unavailable instead of being
masked by another tool on PATH.
The helper never installs Lean, Lake, mathlib, Python packages, Node packages, credentials, services, or MCP servers.
The runtime emits JSON with:
formalization_decisionreasonrequired_definitionsexpected_costrecommended_next_stepformal_check_requirementtool_statuslimitationsThe result can be copied into a v2 evidence.jsonl row or attached as a run artifact, but it does not itself prove the research claim.
When this skill is involved, consider these workflow templates (install via
the workflow-templates artifact profile, or --with-deps to pull backing skills):
informal-to-lean-formalization-runbook -- Local-first intake mapping an informal proof to Lean declarations with a scanner-first verification gate separating typecheck status from claim support.Use when the user asks for a multi-agent discussion, panel review, multi-agent review, or multi-agent research session with role selection, round control, and template-based orchestration.
Use when drafting, validating, or normalizing bounded cross-agent task/result packets for parent-controlled handoffs. This is a packet-contract skill, not a runtime delegation broker.
Send email over SMTP using only the Python standard library, with plain-text and HTML bodies, file attachments, cc/bcc, reply-to, a dry-run preview, connection verification, and redacted config inspection.
Runtime helper for autonomous-research-loop ledgers. Use to initialize, append, validate, inspect, or smoke-test autonomous research loop state files without network, package installation, provider CLI calls, or live agent spawning.
Run bounded autonomous research iterations with evidence gates, recovery ledgers, and optional cross-agent handoffs. Use when the user asks to continue research autonomously, run a research loop, integrate autonomous agent loops, or keep improving a research workflow without repeated prompts.
Use for external DOI/ISBN/title resolution, manifest creation from pasted text, and paper retrieval after the local library-first workflow does not satisfy the request or the user explicitly opts out of library use.