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v1.3.0

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@speakmancip speakmancip released this 14 Aug 13:28
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v1.3.0
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Learn about vigilant mode.

Headline features

1. render_document — server-side document rendering, no local Python or Node required
A new MCP tool converts a Markdown document into a fully self-contained, branded HTML document entirely on the server side — no local script, no Node/puppeteer dependency, nothing the calling client needs installed. This is what unblocks running generate-sad and generate-compliance-report from any MCP client, including ones that can't shell out to a local interpreter at all.

2. Confirmed working: Microsoft Copilot Studio
generate-sad has been run end-to-end inside a live Copilot Studio agent, connected to a local SPEAKMAN.AI server over a tunneled connection. SPEAKMAN.AI's MCP surface was already client-agnostic in principle; this is the first outside-Anthropic client it's been verified against.

Under the hood

  • PDF generation and the local template-directory system (templates/default/, templates/corporate/) are both retired — HTML is the deliverable now, print-to-PDF-able from any browser, with no per-user template setup required.
  • The default document branding is a plain text wordmark rather than an embedded logo image — a full rendered document now runs about 1,400 tokens, down from what an unoptimized embedded logo would have cost (~57,000 tokens for the same document).
  • Fixed a long-standing bug where a workflow step listing more than one agent in its agents array silently ran only the first one — the planner had always been free to bundle multiple agents into a single step, but the engine only ever executed one. Steps are now split and executed individually regardless of how the planner grouped them.
  • Fixed a bug where reaching the HITL review-loop cap discarded the human's final round of feedback and advanced using stale, pre-feedback content instead of the freshly regenerated output.
  • RE_USE_CASE_ANALYST_V1 previously produced exactly one use case per functional requirement by construction; it now enumerates every use case a requirement actually implies (access patterns, CRUD completeness, screen-level states, actor variations), roughly 5x the catalog density on a real test project.
  • RE_DOMAIN_MODELER_V1 and RE_API_SCHEMA_DESIGNER_V1, previously single large agents, are each decomposed into focused sub-agents plus a mechanical synthesis step — reducing single-call cognitive load and the blast radius of any one regeneration.
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