Open-source research & engineering

Verified
swarm engineering

Humans, AI agents, and heterogeneous compute collaborate through bounded tasks, independent verification, and reproducible evidence — because generation is now cheap and trustworthy review is not.

GENERATION — CHEAP GATE OUTCOME candidates · patches claims · proposals verification debt INDEPENDENT VERIFICATION narrow by design verified useful work the only output that counts never the worker’s own word for it rejected retained as evidence, never hidden a negative result is a result a proposal is not proof
The whole project in one picture. Output volume is not the scarce resource. Trustworthy review is — so IDKMesh treats verification capacity, verifier independence, and evidence quality as the constraints to engineer.
Research preview — not production software

What IDKMesh is

An open-source research and engineering project asking whether a large open community of humans and AI agents can discover goals, decompose work, execute bounded tasks, verify results independently, and maintain complex systems better than isolated developers or agents can. It treats that as an empirical question.

Goal → bounded Work Unit → isolated attempts → independent verification → evidence → explicit integration decision.

The project deliberately separates generation from acceptance. A successful worker, a popular proposal, or a large swarm does not automatically become canonical truth. See the six ideas that follow from that →

Five minutes, no account

Try it: audit a review gate

The first installable tool cut from this research measures what a panel of verifiers is actually worth. The finding it packages is an observed one: twenty-five independently seeded test oracles, run over a real 72-candidate corpus, were measured to be worth about one — and the standard N/(1+(N−1)ρ) correction overstated even that by 1.66×. Growing the panel bought nothing; changing how the votes were combined cut error 3.7×. Source: E017.

git clone https://github.com/MSKazemi/idkmesh && cd idkmesh
pip install .
idkmesh gate-audit examples/gate-audit/panel-votes.example.json --pretty

What that command prints is not the E017 measurement. The bundled example is a small hand-authored input that labels itself "evidence_class": "synthetic" in its own output: fifteen candidates, five invented reviewers, 1.69 effective votes from a nominal five against a heuristic 3.66, and two of three seeded known-bad probes accepted. It shows you the shape of the answer. Point the tool at verdicts you actually collected to get an observed one. The contract is Gate Audit v0.1, and the audit is diagnostic only — it grants no acceptance or merge authority. Full quickstart, with the output explained →

What has actually been measured

Every number below is an observed measurement from E017, produced by code in this repository that you can re-run. A verifier there is a partial test oracle — a program, not a person and not a language model — and ground truth comes from executing hidden tests. Most results elsewhere on this site are synthetic mechanism tests, and are labelled as such.

1.66×
how much the standard N/(1+(N−1)ρ) correction overstated that same panel — it said 1.66 effective verifiers where the measurement said 1.00.
0.587
mean pairwise error correlation across 300 pairs of 25 independently seeded test oracles — programs, graded on real defects (E017). Not a knob set by hand.
1.00
effective panel size of those 25 oracles under majority vote — panel error 0.2083 against a single verifier's 0.2044. Growing the panel bought nothing (E017).
3.7×
error reduction from fixing the aggregation rule instead — 0.2083 → 0.0556, with an irreducible floor no quorum reaches (E017).
Read this honestly

Implemented infrastructure is evidence of a capability to run experiments — not evidence that the research hypotheses are true. Most results on this site are synthetic mechanism tests, clearly labelled as such, and the negative ones are kept. The full experiment atlas, with each result's status →

Why now

Pressure

Agents generate faster than anyone can review

Generation capacity is growing faster than trustworthy review capacity. IDKMesh treats verification debt and evidence quality as first-class constraints rather than an afterthought.

Failure mode

Different agents fail together

More votes are not automatically more independent evidence. The project measures verifier reliability, dependence, and failure correlation — and has found the standard correction optimistic exactly where it matters.

Method

The repository is the laboratory

Bounded work, public evidence, reproducible decisions, and community growth measured without Goodharting activity counts. Negative results stay in the tree.

Pick a path

You do not need to understand the whole repository to do something useful in it. Check a task's assignees and recent comments before claiming it.

What exists, and what does not

The project keeps these two lists apart on purpose. Both are maintained in the repository README.

On main today

  • versioned WorkUnit contracts, with work-unit-v0.2 as the current semantic task contract;
  • ResultManifest, EvaluatorPlan and VerificationResult contracts that separate worker claims, verifier evidence and integration authority;
  • cross-object provenance and integrity validation;
  • protocol-neutral worker adapters plus A2A/MCP bindings and conformance helpers;
  • zero-project-spend compute admission and routing experiments;
  • IDKGraph repository modelling, observability and link-integrity machinery;
  • an installable idkmesh CLI whose gate-audit command packages the measured verifier-panel results as a review-gate diagnostic;
  • protected main with the PR gate required on Python 3.11 and 3.13.

Not yet a finished capability

  • no claim that IDKMesh can safely coordinate thousands or millions of real machines;
  • the reference Verified Swarm Runner is not a polished install-and-run product with multiple production worker adapters;
  • canonical real-node integration remains behind its independent-review and evidence gates;
  • A2A/MCP support is an interoperability layer, not a claim that every external agent framework is production-integrated;
  • autonomous repository and community actuation stays policy- and authority-gated;
  • benchmark infrastructure is not scientific proof until controlled observed runs exist.

Explore

The operating principle

Optimise verified useful work per unit of scarce human attention and compute — not commits, agent count, stars, or activity volume.
A proposal is not true because it came from a strong model, many models, an expert human, or a popular repository. Evidence must survive independent scrutiny.

IDKMesh is intentionally unfinished. The repository is the public laboratory, and well-supported disagreement is a contribution. If you can improve a question, falsify an assumption, reproduce an experiment, write a test, find a security problem, make a contract clearer, or reduce reviewer burden, you can contribute.