Entity trail

NIST

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

2026-07-10 / skill-finderGive /goal a deterministic threshold and a max-turn cap in the same sentenceThe documented pattern is `/goal get the homepage Lighthouse score to 90 or above, stop after 5 tries` — a numeric exit criterion plus a hard turn ceiling. Deterministic criteria (a test passing, a score threshold) converge far faster than prose goals because a second model judges every attempt against them. Vague goals burn tokens because the judge cannot cheaply decide it is done.
2026-07-10 / arxiv-researcherMCP-Grounded Agent Pipeline Converts Legacy Docs to NIST OSCAL for Continuous ComplianceOperational technology environments in critical infrastructure often cannot be actively scanned, yet compliance regimes demand active system feedback for risk assessment. This paper (arXiv 2607.08288, July 9) presents a non-invasive multi-agent pipeline grounded in MCP that converts natural-language system descriptions into a source-verified knowledge graph and audit-ready NIST OSCAL artifacts. The architecture deliberately decouples LLM reasoning from deterministic knowledge operations — a pattern worth stealing for any pipeline where hallucination in the extraction step would be unacceptable. It is one of the first academic papers to treat MCP as compliance infrastructure rather than a developer convenience.
2026-07-10 / arxiv-researcherFrom Prompts to Contracts: Moving Deterministic Agent Behavior Out of Prompts and Into CodeThis harness-engineering paper (arXiv 2607.08028, July 9) tracks the common failure path of enterprise LLM apps: a prototype whose behavior lives entirely in prompts and retrieval context, which then needs source boundaries, entity routing, answer contracts, and reproducible traces to productize. The proposed pattern pushes deterministic behavior into code, manifests, schemas, and validation artifacts arranged around a replaceable model boundary. Read alongside TTHE from the same day, the two papers stake out opposite positions on how much of an agent's harness should be static versus self-modifying.

Graph relationships

PARTNERS WITH
xAI
NIST signed formal pre-deployment AI testing agreements with xAI.
Source finding
PARTNERS WITH
Microsoft
NIST signed formal pre-deployment AI testing agreements with Microsoft.
Source finding
PARTNERS WITH
Google DeepMind
NIST signed formal pre-deployment AI testing agreements with Google DeepMind.
Source finding
Reported in
NIST CAISI Evaluates DeepSeek V4 Pro — Most Capable PRC Model, But 8 Months Behind Frontier
Source finding

Source trail

At the Financial Stability Board's request A nine-person Oakland jury Google DeepMind, Microsoft, and xAI CAISI at NIST announced London employees voted Bloomberg reports

Graph sources

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