Skip to content
Agent Orchestration
Skill

/obtain-immediate-conclusions

Derive immediate mathematical consequences from a theorem statement or subgoal. Use when starting a new problem, branch, or subgoal, or when cheap progress or a cleaner reformulation is needed before deeper proof search.

From plugin
danus
16017 skills20 agents3 MCP
Install
$ npx -y skills add frenzymath/Danus --skill obtain-immediate-conclusions --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/obtain-immediate-conclusions

Context preview

The summary Claude sees to decide when to auto-load this skill.

Derive immediate mathematical consequences from a theorem statement or subgoal. Use when starting a new problem, branch, or subgoal, or when cheap progress or a cleaner reformulation is needed before deeper proof search.

SKILL.md

obtain-immediate-conclusions.SKILL.md
name: obtain-immediate-conclusions
description: Derive immediate mathematical consequences from a theorem statement or subgoal. Use when starting a new problem, branch, or subgoal, or when cheap progress or a cleaner reformulation is needed before deeper proof search.

Obtain Immediate Conclusions

Extract direct implications before speculative reasoning.

Input Contract

Read from memory and current context:

  • `problem_id`
  • current theorem/subgoal statement
  • memory

Procedure

1. Normalize notation and restate the claim in equivalent forms. 2. List direct consequences that follow from definitions and basic algebraic/logical manipulations. 3. Split consequences into necessary conditions and candidate sufficient conditions. 4. Mark each consequence with confidence and justification type. 5. For every conclusion, explicitly decide whether it is likely fragile and should be stress-tested by counterexample. 6. If a conclusion is fragile, record why it is fragile and indicate that `$construct-counterexamples` should be considered next.

Output Contract

Publish each conclusion to global memory with `gm_add` (kind `conclusion`): `claim` = the conclusion's statement, `evidence` = the derivation/justification that makes it checkable, and carry these fields in the record:

{
  "statement": "...",
  "justification_type": "by_definition|calculation|known_fact|logical_equivalence",
  "confidence": 0.0,
  "is_fragile": false,
  "fragility_reason": "",
  "suggested_followup": "none|construct-counterexamples",
  "scope": "global|branch|subgoal",
  "branch_id": "optional",
  "subgoal_id": "optional"
}

Rules:

  • `is_fragile` must always be present.
  • If `is_fragile=true`, then `fragility_reason` must explain the risk and `suggested_followup` should be `construct-counterexamples`.
  • If `is_fragile=false`, use `fragility_reason=""` and `suggested_followup="none"`.

Tools

  • `gm_add` (publish the conclusion finding)
  • `gm_search` (recall related findings across the swarm)
  • `search_arxiv_theorems` for nontrivial consequences
  • Codex built-in web search for background definitions/terminology

Failure Logging

If no meaningful consequence is found, note it in your local memory (`events`) with:

  • `event_type="immediate_conclusions_stalled"`
  • missing assumptions and suspected blockers
Read more
Ships withdanus

Danus orchestrates mathematical reasoning agents with fact-graph memory. A main agent (Claude Code) steers a swarm of autonomous codex workers that prove; a cold-start verifier is the sole authority on correctness: a result becomes real only once it passes.

Get the whole plugin

Other skills on danus.