CipherClaw
Deterministic multi-agent debugger with zero LLM calls in the analysis path: causal graphs, weighted root-cause scoring, and failure prediction.
Proof ledger
- Classification
- Built artifact
- Repository
- Alexi5000/CipherClaw
- Language
- TypeScript
- Licence
- Apache-2.0
- Status
- Maintained
- Tests
- 3 recorded gates
- Last verified
- 2026-06-22
- Related write-up
- alexcinovoj.com
What it is
CipherClaw reads agent traces and explains failures without asking a model what went wrong. Analysis is deterministic, so the same trace produces the same verdict every run, which is the property you need when a post-mortem has to be defensible. It ships with zero runtime dependencies.
Architecture
- Trace ingestion builds a causal graph of tool calls, retries, and state transitions.
- Weighted root-cause scoring ranks candidate causes deterministically instead of asking a model to guess.
- Failure prediction flags trace shapes that historically preceded a fault.
- Ships as an OpenClaw plugin (openclaw.plugin.json) as well as a library.
Tests and gates
- The README states 206 zero-mock tests; vitest.config.ts drives the suite and .github/workflows/ci.yml runs it.
- Zero runtime dependencies, so the dependency surface under test is the code itself.
- Examples directory contains runnable traces used by the suite.
Limits
- Deterministic analysis only reports what the trace records. Missing instrumentation stays missing.
- It explains failures; it does not repair them.
- Scoring weights are tuned for agent traces, not for general distributed-systems tracing.
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
ClawKeeper →
Governed Claude agent control plane. A deterministic policy engine runs before every LLM call, autonomous spend defaults to zero, and the audit log is enforced by the database.
TechTide Harness Kit →
Trust contracts for agent skills expressed as JSON Schema: risk tiers, tool permissions, deny-by-default egress, approval gates, and prompt-injection fixtures behind a wall of CI validation gates.
Swarm 357 →
357 Claude agent roles across six business layers, with portable memory, enforced cost caps, a bash policy gate, and durable checkpoints.
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.
Production Block Call at TechTide AI→© 2026 Alex Cinovoj · TechTide AI · Columbus, OH