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Built artifact

Swarm 357

357 Claude agent roles across six business layers, with portable memory, enforced cost caps, a bash policy gate, and durable checkpoints.

Proof ledger

Classification
Built artifact
Repository
TechTideOhio/swarm-357
Language
Python
Licence
Apache-2.0
Status
Active development
Tests
4 recorded gates
Last verified
2026-08-02

What it is

Swarm 357 is an orchestration runtime for a large role library. The interesting part is not the agent count, it is the controls: cost caps are enforced rather than advisory, shell access passes a policy gate, and runs checkpoint so a crash resumes instead of restarting.

Live product

Architecture

  • Role library of 357 agent definitions grouped into six business layers.
  • Portable Memvid memory so context survives process boundaries.
  • Enforced per-run and per-agent cost caps.
  • Bash policy gate mediates shell access rather than granting it wholesale.
  • Durable checkpoints in the database directory allow resume after interruption.
  • FastAPI service surface, Docker image, Railway deployment target.

Tests and gates

  • Four GitHub Actions workflows: ci, codeql, publish, and publish-image.
  • An evals directory is checked in alongside the runtime.
  • gitleaks configuration guards against credential leakage in commits.
  • STATUS.md and ROADMAP.md record what is complete and what is not.

Limits

  • Role count is a capacity figure, not a performance claim. Concurrency in a given run depends on budget and host.
  • Cost caps bound spend; they do not bound wall-clock time.
  • Memory portability is scoped to the Memvid format used by the runtime.

Source artifacts

Patterns applied

Acceptance tests for agent work

Define done before the agent starts.

Evals that gate releases

A golden suite in CI, not a spreadsheet.

MCP permission scoping

Deny by default, declare every tool.

Observability for agent runs

One trace ID from request to receipt.

Cost controls that actually stop spend

Ceilings enforced before the call, not after the invoice.

Approval gates that suspend the run

Nothing downstream executes before a human approves.

Related proof

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CipherClaw

Deterministic multi-agent debugger with zero LLM calls in the analysis path: causal graphs, weighted root-cause scoring, and failure prediction.

FintheFinder

Deep-research agent whose runs suspend until a human approves, with a deterministic citation audit that keeps AI out of the verification path.

This page is implementation proof only. Engagement scope and pricing live on TechTide AI.

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© 2026 Alex Cinovoj · TechTide AI · Columbus, OH