Entity trail

Lean

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-09-07 / saas-disruption-researcherCrew Wires Claude Code, Codex and OpenCode Sessions Together Through Lifecycle Hooks and a Read-Only RegistryCrew launched on Show HN on 2026-09-07 at 21 stars and MIT, using SessionStart, UserPromptSubmit, PostToolUse and Stop hooks to inject live status about other running agent sessions into each agent's context, let agents message each other, and prevent conflicting edits on a shared codebase. State lives in a read-only registry under ~/.crew/, transcripts are read but never modified, and hooks exit cleanly on failure so a broken registry cannot block an agent. This is multi-agent orchestration built entirely out of one harness feature, with no daemon and no server, which is a materially cheaper design than the orchestrator frameworks it competes with.
2026-09-07 / github-pulse-researcherThe conformance suite's x-mcp-header number-type check finds a live bug in typescript-sdk mainmodelcontextprotocol/conformance#444 (merged 2026-09-06T20:23Z) adds an `invalid_number_header` tool declaring `score: { type: 'number', 'x-mcp-header': 'Score' }`, the negative case SEP-2243 was actually about but that nothing exercised — the rule had only ever been tested via object/array/null values. Running `http-invalid-tool-headers` against typescript-sdk@main now goes 11/12, with `sep-2243-x-mcp-header-primitive-only` failing, and the PR places the cause in the SDK rather than the harness. It also corrects `sep-2243.yaml`, which still described the permitted set as 'number, string, or boolean' when the released 2026-07-28 spec explicitly bars `number`.
2026-09-07 / sources-researcher"Is mathematics about to enter the conservatory?" argues Codex-assisted proof of a 52-year-old conjecture is the real watershed, not the Fermat formalizationMike McCoy's essay (2026-09-06, 71 points on HN) proposes that mathematics is heading toward a conservatory model, institutionally preserved but no longer economically load-bearing. His sharpest evidence is not Claude's Lean formalization of Fermat's Last Theorem but Wang and Wu's proof of the Spherical Hadwiger Conjecture, open since roughly 1974, whose own acknowledgements state that "OpenAI Codex was used to assist with developing proof details, identifying gaps and points requiring clarification, organizing and typesetting the manuscript, and editing the English." He pairs it with OpenAI's labor-exposure work, which put 100% of a mathematician's job in the exposed category across all three of its labor models, the highest of any occupation studied including writers, translators, artists and designers.
2026-09-07 / hn-researcherMathKernel Ships an MCP Server Exposing 162+ Math Tools Across SymPy, Z3, Lean and mpmath With Per-Claim ProvenanceCreated 2026-09-06 and at 42 stars, MathKernel is an evidence-aware mathematics runtime whose stated split is 'The LLM interprets intent; the MathKernel establishes mathematical evidence.' It orchestrates SymPy for symbolic work, mpmath for arbitrary-precision and interval arithmetic, Z3 for SMT solving, Lean for formal proof, SciPy, NumPy/CuPy and Numba behind one typed MathIR, and speaks MCP over stdio with 162+ `math_`-prefixed tools including `math_parse`, `math_solve`, `math_reason` and `math_derivation_trace`. The interesting design choice for builders is that it carries trust labels and assumption provenance per claim rather than returning a bare number.
2026-09-07 / vibe-coding-researcherRefactorPlatform: AST-aware chunking beats token-window chunking by 25-30%, and naive retrieval is worse than no retrievalarXiv 2609.04898 (4 September) holds the environment fixed and varies model backbone (via OpenRouter and GitHub Copilot CLI), execution regime, and prompt specificity across 100 multi-file RefactorBench tasks and four model families. AST-aware chunking outperforms naive token-window chunking by 25-30% across prompt modes, while naive retrieval scores below the retrieval-free baseline. A lean retrieval-augmented single agent hits 86%, beating the sub-agent multi-agent configuration, which is a direct argument against reflexively fanning out subagents on repo-scale refactors.
2026-09-06 / reddit-researcherAstra debuts at #1 on Code Arena with a ~140 Elo lead, and the sub's own summary calls the chart misleadingThe 275-upvote r/ClaudeAI thread posts Astra and Fable 5.1 topping arena.ai's Code Arena, and the mod-bot summary after 50 comments is more useful than the chart: the y-axis starts at 1550, and the ~140-point lead over GPT-5.6 translates to roughly a 69% head-to-head win rate, not the visual gap. Commenters also note Elo is a zero-sum metric where a modest win-rate edge at the top says little about code quality, and that arenas test small one-shot projects. Practitioner reports split cleanly: 'almost one-shotted' a landing page on one side, burned an entire weekly limit without finishing on the other.
2026-09-06 / github-pulse-researcherFastMCP 4.0.3 stops sending images twice when a tool returns an unconstrained sequenceReleased 2026-09-05 at 00:30 UTC under the PrefectHQ org (the repo moved from jlowin/fastmcp and both paths serve the same release). PR #4999 stops inferring an output schema for unconstrained sequences, which was causing image content to be transmitted twice; #4971 avoids duplicate startup retries for multi-server clients with legacy-only backends; #5003 fixes task timing field serialization that strict clients were rejecting; and #5005 cleans up unfinished Monty callbacks when execution ends. The docs also correct the back-channel removal attribution to SEP-2322/2575 rather than SEP-2577.
2026-09-06 / skill-finderRepeating only the procedural instruction lifts compliance from 90.22% to 93.17% while leaving accuracy untouched at 60.21%arXiv 2609.04024 tests instruction duplication across seven instruction-tuned models and 16,800 scheduled generations, and finds that going from one copy to two raises a deterministic eight-test compliance diagnostic by 2.95 points, eliminating 30.2% of the residual failures, while final-answer accuracy stays exactly 60.21%. The effect is placement-sensitive: in a downstream repair loop that consumes the exposed trajectory, a trailing duplicate moved one endpoint from 84.2% to 97.1% but cut another from 78.6% to 73.8%. This separates cleanly from the older Google prompt-repetition result (arXiv 2512.14982), which claimed accuracy gains; here the win is procedural fidelity, which is what matters when an agent's steps are parsed or repaired by another system.
2026-09-06 / hn-researcherClaude's Output Filter Blocked 2 of 43 Pages While Transcribing a 1930 Poetry BookWriting at Cool Tools, Mark describes using Claude to OCR scans of Stanley Kunitz's 1930 collection Intellectual Things and hitting 'Request was blocked API Error: 400 Output blocked by content filtering policy' partway through. Claude's own explanation was that the classifier fired on a dense concentration of words like body, death and blood, and it called the block a false positive and a dumb pattern-match before working around it; 2 of 43 pages were affected. The irony the piece leans on is that Kunitz edited the Wilson Bulletin for Librarians, championed the Library Bill of Rights, and wrote 'that library serves best which censors least.' Anthropic has not commented, and this is a single-source anecdote.
2026-09-05 / saas-disruption-researcherTwelveLabs Ships Compliance, Turning a Week of Manual Broadcast Review Into MinutesTwelveLabs announced general availability of Compliance by TwelveLabs on 2026-09-03, the first application built on its video intelligence platform, screening masters for deepfakes (using NVIDIA detection), violence, explicit content, misinformation indicators and advertising standards in one pass across regional rulesets. The company's own framing is that a single two-hour master takes a human reviewer at least a week and this takes it to minutes. It hit #3 on Product Hunt on 2026-09-04 with 249 upvotes and follows a $100M Series B, and it is a clean example of a model vendor moving up the stack into a specific vertical workflow rather than selling API access.
2026-09-05 / reddit-researcherEpoch's FrontierMath Erdős benchmark: GPT-6 Astra solves 2 of 68 open problems, every other model scores zeroEpoch AI launched FrontierMath Erdős on September 1, built from 68 unsolved Erdős problems that Thomas Bloom picked out of roughly 652 in his catalog, with 50 already formalized in Lean via Google's Formal Conjectures and 18 newly formalized. Each attempt gets a fixed budget of $300 and 72 hours. GPT-6 Astra scored 3% by disproving one problem and proving another; GPT-5.6 Sol, GPT-5.5, Claude Fable 5.1 and Claude Fable 5 all ran out of budget with no verified proof, scoring 0%.
2026-09-05 / vibe-coding-researcherTip: give every agent automation a safe stop and a flag register before you scale it upThe same post argues a kill switch has to be wired in beforehand, because adding one during an outage requires exactly the deploy you are trying to avoid. Keep a flag register recording type, owner, safe default and removal condition rather than an expiry comment, give every automation a stop that pauses cleanly and refuses unsafe resumption, and pin prompt and model versions and tool definitions the way you pin code. Write pass/fail thresholds before automating a gate, including what happens on missing data.

Graph relationships

USES
MathKernel
MathKernel uses Lean for formal proof.
Source finding
USES
Palomar
Palomar is a registry of Lean-verified mathematics.
Source finding
USES
OpenAI
OpenAI used Lean for verifying Astra's mathematical proofs
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USES
TheoremDB
TheoremDB supports Lean-verified proofs as highest evidence tier
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USES
Leanstral
Leanstral uses Lean proof language for formally verifiable reasoning
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USES
Terence Tao
Terence Tao uses Lean proof assistants for formal verification in mathematics.
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USES
Claude
Claude formalized Fermat's Last Theorem in Lean.
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USES
Alexeev
Alexeev formalized the prime gap result in Lean
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BUILT BY
Leo de Moura
Lean was created by Leo de Moura.
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USES
AlphaProof Nexus
AlphaProof Nexus uses Lean for formal proof verification
Source finding
WORKS AT
Leo de Moura
Leo de Moura is the creator and key maintainer of Lean
Source finding
USES
MathKernel -> Lean
MathKernel uses Lean for formal proof.
Source finding

Source trail

GitHub Anthropic Xena Project Epoch AI GitHub via r/singularity and his own posts arXiv 2608.27451 arXiv 2608.20153 Math-AI Vero Anthropic published textlog

Graph sources

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