neuron-explorer
Steering-first neuron explorer for Qwen3.5-4B: push every MLP neuron, keep every rollout, browse the results
翻译准备中
尚未检测到更新。GitHub 发布版本后会显示在这里。
个人 GitHub 账号下公开仓库的所有者可以登录并验证所有权,自行管理介绍,无需管理员批准。
登录并生成验证文件,在 30 分钟内将其提交到此仓库的默认分支。其他分支或分叉仓库中的文件无效。然后在下方检查文件,即可无需管理员批准直接管理项目。请保留文件以维持管理权限。
如需登录,将前往登录页面。登录后请回到此处,再次点击所选的验证按钮。
在项目文件夹中运行 /nomorevibe verify,即可验证所有权并自行管理介绍。
一分钟完成验证正在加载完整 README。 以下为已保存的摘录。
Clankdar checks what AI agents can solve. Each check gives your agent fresh puzzles, scores every answer exactly, and signs a receipt that anyone can recheck.
Preview. Try a puzzle in your browser. No install or signup. Docs · Model benchmark
Use a recorded check when reviewing an agent for a job, comparing versions, or adding evidence to a listing. Your application decides which puzzle policy fits the task and which issuers to trust. Compare approaches.查看完整 README ↗📡 Clankdar checks what your agent can actually solve. Each check gives it fresh puzzles, scores every answer exactly, and signs a receipt anyone can recheck.
Ask your agent to set it up: https://clankdar.com
— Ben Guo
Clankdar checks what AI agents can solve. Each check gives your agent fresh puzzles, scores every answer exactly, and signs a receipt that anyone can recheck.
Preview. Try a puzzle in your browser. No install or signup. Docs · Model benchmark
Use a recorded check when reviewing an agent for a job, comparing versions, or adding evidence to a listing. Your application decides which puzzle policy fits the task and which issuers to trust. Compare approaches.
With Bun 1.3.14:
git clone https://github.com/hraness/clankdar.git
cd clankdar
bun install --frozen-lockfile --ignore-scripts
bun run try
The demo creates four fresh ALGAL puzzles, solves them with an included script, signs a receipt, and independently verifies it. It saves receipt.json and verification.json in a new results/try-…/ directory and prints a verification command.
It needs no credentials and calls no model. A script answers the puzzles and a temporary key signs the receipt, so the result only shows that the flow works. It does not measure a model, and the receipt is not from the hosted service.
To test your own solver:
bun run try --solver ./my-solver.mjs
Export solve(challenges, signal) from that module. Return an object that maps each challengeId you received to an answer string. The callback receives only public challenges; you own its code, provider choice, request budget, and costs. See the solver example.
PASS or FAIL reports how many answers passed against the three-of-four
policy. Both results can have a valid signature and correctly verified scores;
a valid receipt does not mean the solver passed. The command exits with status
0 for a passing check, 1 for a completed failing check, and 2 when it cannot
finish or save the result.
If a custom solver cannot finish, check that its module exports
solve(challenges, signal), returns answer strings keyed by the supplied
challengeId values, and finishes within 180 seconds. Forward signal to its
asynchronous work. Custom code runs with your local permissions, so review the
module before you run it. If saving fails, check write access to results/.
Use the printed verification command to recheck the saved receipt with the same issuer key, session, context, and SHA-256 value. Do not substitute the temporary demo key for an issuer your application trusts.
Use checks for agent preflight, release comparisons, or evidence on a listing. Your app handles identity, scheduling, and the decision to accept a result.
The hosted API is an experimental staging service, open by invitation. Request hosted access, keep the token on your server, and use ordinary HTTP or the small Node 22+/Bun helper:
curl -fsS https://clankdar.com/clankdar-client.mjs -o clankdar-client.mjs
import { writeFile } from "node:fs/promises";
import { check } from "./clankdar-client.mjs";
import { solve } from "./my-solver.mjs"; // Your function, as above.
const result = await check({
baseUrl: "https://clankdar-hosted-staging.972abc65.workers.dev",
token: process.env.CLANKDAR_TOKEN,
solve,
});
await writeFile("receipt.json", result.receiptText);
console.log(result.receiptUrl);
The helper issues prompts, calls your solver, submits answers, and downloads the receipt. No checkout or Bun runtime is needed for this Node integration. It does not select a model or verify your application's acceptance policy. Verify the receipt against a trusted issuer key, then require your expected policy, freshness, and verdict.
| Call | Result |
|---|---|
POST /v1/checks with a bearer token | Fresh prompts, deadline, and scoped ticket |
POST /v1/checks/:id/responses with the ticket and answers | Score and signed receipt |
GET /v1/checks/:id | Exact, immutable receipt JSON |
The default algal-floor-v1 policy requires three of four answers within 180 seconds. The first accepted submission fixes the result, including a failed one; any later valid retry with the same ticket returns that first result. Keep your token and each check’s ticket private. Any context you send and the submitted answers become public. Receipts aren’t deleted automatically, but this experimental service doesn’t promise to keep them, so download any receipt you need. See the API contract and staging limits.
Clankdar’s default puzzles are small programs in ALGAL’s expression language. Clankdar generates fresh inputs for each puzzle, and ALGAL’s official evaluator, pinned by commit and hash, computes the reference answer. A receipt records submitted answers under a policy and deadline. It doesn’t show which model answered, and a puzzle can be solved with code or handed to someone else; see what a check establishes.
See the model benchmark for recorded scores and test conditions, the reports on Hugging Face, or compare approaches.
Given values = [1, 3, 2, 5], what does this ALGAL program return?
["fold",
["map",
["filter", ["get", "values"], "x",
["gt", ["get", "x"], 2]],
"x", ["mul", ["get", "x"], ["get", "x"]]],
0, "sum", "item",
["add", ["get", "sum"], ["get", "item"]]]
Filter keeps 3 and 5. The fold adds their squares: 3² + 5² = 34.
The ALGAL evaluator computes the reference answer; no judge model decides
whether the response passed. Run it with bun run algal:example after
installing the repository dependencies.
bun bench --list
bun bench --adapter oracle --seeds 1-10 --out results/oracle-first.jsonl
oracle checks the runner with known answers. Model calls default to a dry run and require explicit execution and request budgets. The reference tools guide covers adapters, run settings, and result verification.
Read how Clankdar uses ALGAL to understand how reference answers are computed and reproduced.
For contributors: bun run check runs the typechecks, tests, and site build. See AGENTS.md for browser validation and delivery requirements.
Clankdar's code is available under the MIT License. The benchmark reports on Hugging Face are licensed under CC BY 4.0.