io.github.IamHarrie-Labs由 GitHub 账号 IamHarrie-Labs 发布v2.0.1更新于 Nov 5, 2026
Can this position be closed, and what does it cost? Executable quote first, model beside it
远程 MCP 工具，估算按指定规模退出某个加密代币仓位的成本，以及不超出滑点上限的最大规模。
Web executable，通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。
把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体，或 SourceWeft 对话中。智能体会读取该服务器的安装指南，先向你展示发布者、端点和登录方式，经你同意后再把它添加到你的客户端。密钥不会写进任何命令。
阅读 https://sourceweft.com/mcp/io.github.IamHarrie-Labs%2Fhanko/install.md，并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前，先告诉我它的发布者、端点和登录方式，等我确认。不要把 API 密钥写进命令或我会提交的文件；问我密钥应从哪里获取。把它添加到你客户端的 mcpServers 配置中。
{
"mcpServers": {
"hanko-exit-liquidity": {
"type": "http",
"url": "https://tryhanko.xyz/api/mcp"
}
}
}Hanko turns crypto market chatter into a sized position, or an honest refusal, with the evidence attached, and can prove that same decision byte for byte, years later.
Point it at a token and the voices you trust, on X, Telegram or Bluesky. It reads what each one actually said, checks whether they're independent voices or one thesis repeated three times, and decides:
Sample output: real engine, synthetic inputs. voice_alpha/voice_beta/voice_gamma and TOKENA are fictional test fixtures. None of them is a real account or token.
Run that same input again in a year and it produces the identical decision id, because nothing about deciding touches the network, a clock, or a model. It only ever reads what was actually stored. That is the whole project: "prove it" is a command you can run.
Judging? Start at /judges: every line of
the published rubric, mapped to a page or command you can check yourself.
tryhanko.xyz has the pitch and a sample
receipt (synthetic inputs, labelled). /try runs a piece of it, live,
from your browser, no install. Full technical detail is at /docs.
RYO-CHAN Hackathon 2026 submission, three tracks. Track 1 (Autonomous
Agents) is the agent above, built to the Multi-KOL Narrative Agent spotlight.
Track 3 (New Skills) is exit_liquidity:
what it costs to get out of a position, from an executable venue quote where
one exists, in RYO's own response envelope. It is also the size gate the agent
runs before committing. Track 2 (Dashboards & Interfaces) is three screens:
the workbench, the
failure drill and the
Echo Index.
live/. Every decision is graded
72 hours later against the conditions it wrote down first.
/ledger shows what changed since the
last run, most important first (D-20).runs/run_836b976720f63dc0.json. The manifest lists every watchlist entry,
including the PASS and both ABSTAINs. It is anchored in Bitcoin block
972,817, mined 35 minutes after the seal, and hanko verify-run replays
all four decisions from the committed bundle with no network and no key.
(Until 2026-10-24 that bundle was not actually in the repository; D-19.)A 判子 is the seal a person stamps on a document to commit to it. The mark goes on before the outcome is known and can't be taken back, which is exactly what this agent does with every decision it makes: sizes it, commits to it, and states in advance what would prove it wrong.
No live credential, no account, no network. Every number below regenerates from synthetic fixtures committed in this repository (fictional sample voices and a fictional token, written for testing):
Builders and traders who want an agent's reasoning to be auditable rather than taken on faith. Someone who has been burned by a bot that says "strong buy signal" with nothing behind it, and wants to see the evidence, the falsifiers, and the honest gaps instead. Also the judges reviewing this submission, who can replay any decision from the exact stored bytes it saw.
Not built for anyone who wants the agent to execute trades. It doesn't, and by the hackathon's own rules, none of the RYO tools it's built on can either. Everything here researches and sizes a position; nothing here moves funds.
The agent only ever sees the output of parse(). Because parse() is pure and
payloads are content-addressed, any past decision can be re-derived from stored
bytes and must reach the same verdict. Put a network call inside parse() and
the reasoning trail stops being reproducible, and that property is what the
whole submission rests on.
Full tree:
Sources are interchangeable. The agent never learns where a piece of
evidence came from. Swapping X for Telegram, or Grok for a direct API, changes
one adapter and nothing downstream. If x_search is deprecated or priced out on
day 9, nothing else moves.
That swap is a real option. X's own API returns structured posts directly, with no model paraphrasing a prose summary in between, at the cost of a separate paid tier and a different credential than the one this build already has. Worth doing later; not worth the rewrite risk this close to submission when the adapter boundary already makes it cheap whenever it happens.
Failure is recorded as data. A source that was asked and did not
answer produces a FAILED snapshot with the reason attached. An adapter that
raises produces one too. Silence is the single outcome this store cannot
represent, which is what lets position sizing respond honestly to missing evidence.
Three different kinds of nothing stay distinct. FAILED (the source did not
answer), OK with zero items (nobody posted), and PayloadShapeError (bytes
arrived that we cannot read) are separate facts. Collapsing them would let a
schema change look like a quiet market.
Coverage is never overclaimed. x_search is a search tool. It cannot list a full timeline, so its coverage is UNKNOWN by construction. Claiming COMPLETE is
precisely the lie that would inflate a convergence count across KOLs.
Collect once, develop free. Real snapshots are captured once and everything afterwards runs against stored bytes. Development and CI cost nothing and hit no rate limit. At an hourly sweep over 20 handles, live collection runs about $0.005/call, roughly $25 to $35 for the whole build.
Offline, against a fixture:
XAI_API_KEY must be set for live X collection. Without it the adapter records
a FAILED snapshot saying so and carries on.
352 tests, all offline, ~20s. Covered at the evidence layer: canonical form and address stability, payload deduplication, tamper detection, adapter-version mismatch on replay, replay determinism, evidence identity pinned to bytes and position, and each failure mode (rate limit, partial window, empty result, raising adapter, malformed feed, unreadable payload). At the decision layer: echo demotion, PASS vs ABSTAIN separation, mechanical size reduction under missing safety data / a failed source / stale evidence, falsifier generation for both entries and refusals, ledger tamper detection, and end-to-end reproduction of a stored decision from stored bytes. At the review layer: falsifier checking, profit not rescuing a falsified thesis, uncheckable metrics staying unresolved, inconclusive reviews excluded from every rate, echoes earning neither credit nor blame, calibration, and the refusal to re-review a decision.
At the MCP layer: the JSON-RPC handshake, session handling, SSE decoding, every transport failure mode, and a test asserting that facts extracted from an MCP payload are identical to facts extracted from a REST payload.
Confirmed against the live API, 28 Aug 2026. x_search does not return
structured post objects. It returns the model's prose rendering of the posts
plus an array of URL citations. Prose cannot be attributed to a specific post,
so the adapter requests a JSON schema and then verifies every returned post id
against the tool's own citations: cited posts are kept, uncited posts are
dropped. That check proves a post exists and that the tool saw it; it does not
prove the model transcribed the text or timestamp faithfully, so those fields
are flagged as model-transcribed on every item.
Confirmed against the live RYO MCP server, 5 Sep 2026. hanko tools,
hanko facts SOL, and hanko decide have all run against the real endpoint. Three things that changed once the guessing stopped:
The catalog has six tools. The hackathon's public tool list names seven. check_safety and supported_tokens are not on the authenticated
catalog; monitor_market_sentiment_shift is, and wasn't guessed at all.
There is no numeric safety score anywhere in the six, so safety_score on
MarketFacts now stays None every time.
Argument keys are symbol (analyze_token, deep_analysis) and symbols
as one comma-separated string (compare_tokens). Both transports were first built guessing token and are now fixed to match.
The response is {"tool": ..., "result": {envelope}, "latency_ms": ...}
over REST, and the envelope's own status (ok / partial /
unavailable) and data_mode (live / mixed / simulated / unknown)
are what _degraded() now reads. A response that admits to being
simulated is treated exactly like a partial one, since simulated data
presented as live is the one fabrication the platform says it never does.
Correction, 22 Sep 2026. A routine
hanko auditcrashed outright withPayloadShapeError: no message item in the response output. The cause was a labelling bug: a decision built from local fixture data had been tagged with the live X source's own id, so replay handed the real adapter bytes it was never built to read. Every existing replay test had missed it, because each one supplied its own resolver that returned a fixture unconditionally rather than going through the same lookuphanko auditactually uses. Full write-up, the fix, and the regression test that proves it, inDECISIONS.mdD-07.
Not yet shown: a calibration curve from real outcomes, a live ENTER, and a
real priced pool. Stated plainly, with why, in
LIMITATIONS.md.
The six real tools all answer some version of is this worth entering? Nothing answers can this position be closed, and what does closing it cost? That's the number that turns research into a trade. A token can clear every measured signal and still be a trap if exiting the position moves the price double digits.
Live output from 2026-10-23, recorded while RYO's market tools were down. RYO
has never published pool depth, so version 2.0 asks two keyless venues.
DexScreener supplies pools for the token's canonical contract: never searched
by symbol, because that returns impostor pools. Jupiter supplies an executable
quote for the exact size. A measured quote outranks the model, and the
model's error is printed beside it. Where neither venue answers, cost fields
are null, never zero. Every answer is RYO's public response envelope, also
served on RYO's own REST route shape (POST /api/tools/exit_liquidity/call)
and as an MCP server (/api/mcp).
Full model, honesty conventions, and test coverage in
hanko/skills/exit_liquidity/README.md.
Runnable live, against the real platform, at
tryhanko.xyz/try, restricted to
a few tokens and a capped size, so a public page can't turn into an unbounded
tap on a live credential.
.claude/skills/hanko-exit-liquidity/SKILL.md
packages this exact command as a Claude Skill: point Claude Code at this repo
and it can answer "what does it cost to exit this position" directly, scoped
by an explicit rule that every number in the answer has to come from the
command's own output, never invented or rounded by the model. The same
honesty convention the tool enforces on itself, extended to whoever is
running it.
A record states, at the moment of the decision: what was concluded, on what evidence, by what reasoning, what was missing, and what would prove it wrong.
The engine is pure. decide() reads its arguments and nothing else: no
clock, no network, no model call, no randomness. Interpretation is the one
subjective step, so it happens upstream and is frozen into the record. Put an
LLM in the decision path and replay proves nothing.
Three verdicts. ENTER, PASS (the evidence was adequate and
argued against it), and ABSTAIN (the evidence was not adequate to argue either
way). Collapsing the last two would let the agent claim a market view it never
had.
Missing data shrinks the position, mechanically. No rule says "if safety is unavailable then halve". A gap lowers completeness, completeness lowers evidence quality, and quality sets size. The four quality components combine as a weighted geometric mean, so a component at zero takes the whole score to zero. Enthusiasm can't average away an absent safety check.
Agreement is checked for independence. Three accounts quoting one thesis is one observation in disguise, and counting it as three is the easiest way for a multi-KOL agent to be confidently wrong. Every echo is recorded with the post it repeats and the reason it was demoted.
Every decision pre-registers its own falsification. Falsifiers are written
before the outcome is known, evaluate mechanically, and are hashed into the
decision_id. Move a threshold, a size, or a review date after the fact and you
get a different id, so any edit shows as a new decision. Refusals commit too: a
PASS records what would flip it.
Three authors mentioned the token; two of them were independent. Swap in the market fixture with no safety score and the same evidence sizes at 3.08%, down from 3.28%. Nothing in the rules changed, only what was known.
hanko audit re-derives every recorded decision from stored bytes and insists it
reproduces. That is the CI gate that turns "preserves a repeatable reasoning
trail" from a README claim into a failing build.
At review_at, each falsifier is evaluated against observed facts and the
decision is graded against what it committed to. Whether it made money is recorded but does not decide the grade.
Those come apart more often than is comfortable. An entry can be profitable and still falsified: the price rose while the liquidity that justified the size drained away, meaning the reasoning was wrong and the outcome was luck. Both facts are recorded and reported separately. Grading on profit alone is how an agent learns to repeat lucky mistakes.
The third outcome carries the weight. When the metric a falsifier names is
unavailable at review time, the check is UNCHECKABLE, never quietly counted
as passing. A decision that could not be checked is not a decision that was
right. Inconclusive reviews are excluded from every rate and reported as their
own number, because an agent that silently drops what it could not verify is
grading itself on a sample it chose after the fact.
Refusals are graded too. A PASS commits to what would have flipped it, so
an agent that only marks the trades it took never learns what its caution cost.
One review per decision, enforced. Re-reviewing until the answer improves is the exact failure pre-registration exists to prevent, so the ledger refuses a second review.
The liquidity_usd line says exactly what it checked: one reading, no
intermediate ones. price_usd and liquidity_usd are graded against every
sample hanko sweep --samples logs between the decision and the review
(D-13) --
a breach that recovers before review time still falsifies the thesis it
broke, and a review built from a single end-of-window reading says so.
Said 0.7, was right 50% of the time. The agent is overconfident, and says so.
Per-voice reliability is earned from the agent's own audited history. Follower counts play no part, and echoes earn neither credit nor blame. A voice with no scored decisions gets None. Reporting it as zero would defame
it; reporting it as 100% would promote it. Per-rule reliability answers the
uncomfortable question: a rule that is always satisfied on losers is not a
filter, it is decoration.
hanko decide handles one token, from one source, by hand. A real watchlist
needs the same thing done for twenty tokens across several sources on a
schedule, without one dead source or one bad token taking the rest of the
run down with it. hanko/sweep.py is that orchestration.
One pass: decide on every entry in the watchlist, then grade every decision the ledgers say is due. A failing token is recorded in the report and the sweep moves on. A token dropped from the watchlist still gets its outstanding decisions reviewed.
Every snapshot in one sweep is stamped at the sweep's own as_of. The several source calls inside one pass take a few
real seconds, but they all belong to the same logical instant, and a sweep
re-run against unchanged sources should reach the same decision_id, even if the retry lands a second later.
Review takes a fresh look. fresh_observations()
re-collects evidence and re-derives independent_voices at review time. The whole point of a
review is what's true now; a stale copy of "true then" would grade a
decision against itself.
--samples samples.jsonl gives the window something to actually check.
Every pass appends one market reading per watched token, reusing the facts
that pass already fetched. A decision that becomes due later is graded against every reading logged since it was made. That lets an ANY_POINT_IN_WINDOW falsifier
(D-13)
catch a price or liquidity breach that recovers before the clock gets there.
Omit it and hanko sweep keeps the single end-of-window reading it always
took; the review says which of the two it used.
Meant to be invoked by something that already knows how to schedule things: cron, a scheduled GitHub Action, Windows Task Scheduler. Each call does one pass and exits, so a failed run is just a failed invocation.
This repository runs one. .github/workflows/sealed-sweep.yml
seals watchlist.live.json every three hours with no
key at all, then verifies the run from its committed files, upgrades any
pending Bitcoin proofs, and writes live/summary.json for
/ledger:
--interpreter lexicon is the keyword reader taught to recognise "Bitcoin"
as well as "$BTC", matching words whole. --lookback-hours 24 reads only
the last day of a feed, since a Telegram page or an RSS feed keeps days of
history that would otherwise score as stale (D-20).
Sweep tests run offline, using a fixture stand-in for RYO tool responses
(FixtureFactsSource, shaped like the live tool sources) alongside the existing evidence fixtures.
Covered: a failed evidence source or fact tool becoming a recorded gap, one bad token not cancelling the rest of the sweep, a decision
already in the ledger being skipped, a token dropped
from the watchlist still getting reviewed, and review pulling fresh observations.
ARCHITECTURE.md: the one rule, the pipeline as a
diagram, what each package owns, and how exit_liquidity sizes itself as
the same size gate decide() runs internally.DECISIONS.md: 21 engineering decisions in the
order they happened, including several real bugs found and fixed during
this build and what each one actually broke.LIMITATIONS.md: what hasn't been shown yet, stated plainly.SEALING.md: hanko seal -- a numbered manifest of an
entire watchlist run (errors included), anchored to
public OpenTimestamps calendars, published before the outcome is known.Wire sweep, audit, and scorecard into CI or a scheduled run, and feed
per-voice reliability back into evidence weighting so the agent's own track
record starts shaping what it believes.
Hanko 2.0.0 is published in the official MCP registry as io.github.IamHarrie-Labs/hanko.
python scripts/compare_baseline.py.The first successful model-read workflow sealed run_547a6eaf6c69d992 on 30 Oct: 21 model calls, no fallbacks, three unnamed-token readings rejected, and all four decisions independently replayed. Its Bitcoin timestamp is confirmed.
来源：README.md，提交 256a045
Exit liquidity
What it costs to exit a position at a given size, and the largest size that clears a slippage ceiling. Uses an executable venue quote when one exists (basis: quoted) and a constant-product model otherwise (basis: modelled), shows the gap between the two, and returns null rather than zero when an input is unavailable. Returns RYO's public response envelope.
token必填size_usdmax_slippage_pctparticipation_pct已满足适用检查项的 100%
该评分衡量此收录条目的完整程度，依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价，也不表示服务器安全或当前可用：可连通性是带日期的检查结果，评分也不包含安装量或用户评价。
ENTER TOKENA size 3.28% confidence 0.66 + independent_voices: 2 independent voice(s): voice_alpha, voice_gamma ~ echo voice_beta: marked as a repost or quote by the source ! wrong if price_usd < 1.0625 at any point within 72.0h (thesis fails if price falls 15% from entry) review at 2026-08-30T12:00:00Zgit clone https://github.com/IamHarrie-Labs/hanko && cd hankopip install -e ".[dev]"
pytest # 349 tests, offline, ~20s
# make a decision, then prove it replays from stored byteshanko decide x --token TOKENA --subject voice_alpha --subject voice_beta \ --subject voice_gamma --market fixtures/market_tokena.json \ --as-of 2026-08-27T12:00:00Z --fixture fixtures/x_three_voices.jsonhanko audit # re-derives it, insists it reproduces
# the Track 3 skill, against the same fixture, no networkhanko exit-liquidity TOKENA --size 50000 --market fixtures/market_tokena.json
# the first live ENTER, re-derived from its committed bundlehanko verify-run runs/run_836b976720f63dc0.json
# break it on purpose: nine failure scenarios, offlinepython -c "from hanko.drill import run; print([r['held'] for r in run()])"
# re-derive every number in the Echo Indexhanko echo-index publishfetch() touches the network, is allowed to fail, and is never deterministicparse() touches nothing, and is a pure function of its payloadhanko/provenance.py canonical JSON, sha256 addressing, Status, Coveragehanko/evidence.py Evidence + Provenance: the source-agnostic unithanko/sources/base.py the adapter contracthanko/sources/xsearch.py X, via the xAI Responses API and its x_search toolhanko/sources/rss.py RSS/Atom: free, and the only source with trustworthy timestampshanko/sources/fixture.py local JSON: free development, and every failure mode in CIhanko/snapshot/store.py append-only content-addressed store, replay, integrityhanko/ryotools/ the six RYO tools over MCP and REST; structural fact extractionhanko/skills/exit_liquidity/ Track 3: what it costs to exit a positionhanko/review/outcome.py grading a decision against its own commitmenthanko/review/reliability.py calibration, per-voice and per-rule track recordshanko/review/ledger.py append-only reviews, one per decisionhanko/cli.py collect / decide / review / scorecard / audit / verifyhanko/ sources/ X, RSS, fixtures -- fetch() impure, parse() pure snapshot/ append-only content-addressed store ryotools/ the six RYO tools, MCP + REST decision/ evidence quality, verdicts, falsifiers, the ledger review/ falsifier checking, calibration, reliability skills/exit_liquidity/ Track 3: exit cost, capacity, drift, turnover sweep.py, cli.py, config.py, provenance.py, evidence.pysite/ static landing page, /docs, /try -- the live web demo api/exit_liquidity.py the /try endpoint, real assess() call, no fixturetests/ 349 tests, one file per hanko/ packagefixtures/ evidence and market fixtures used offline and in CI.github/workflows/ci.yml pytest on every push, Python 3.11 and 3.12.claude/skills/hanko-exit-liquidity/SKILL.md packages exit_liquidity as a Claude SkillARCHITECTURE.md the one rule, the pipeline, the layersDECISIONS.md engineering decisions and the bugs that shaped themLIMITATIONS.md what hasn't been shown yet, and whyLICENSE MITpip install -e ".[dev]"pytesthanko collect x --subject voice_alpha --subject voice_betahanko collect rss --subject https://example.com/feed.xmlhanko lshanko replay snap_7723f3520b7dfa2efa6856e3hanko verifyhanko collect x --subject voice_alpha --fixture fixtures/x_three_voices.jsonhanko exit-liquidity BONK --size 50000OK BONK confidence high price $0.00000331 · 24h volume $1,395,538 (dexscreener) quoted: selling ~$50,000 on jupiter returns $48,886, 2.34% under its own near-mid rate (price impact plus fees, 5-hop route) model said 7.15% from $1,299,172 of on-chain depth the model overstates this exit's cost 3.1x: the route reaches concentrated liquidity a constant-product curve cannot see depth: 29 pools on solana, deepest $327,472, 1 rejected or exit over 8.6h at 10% of volume verdict from an executable jupiter quote; quotes move with the markethanko/decision/reading.py interpretation, recorded once and frozenhanko/decision/convergence.py independence: is this many voices, or one echoed?hanko/decision/quality.py gaps, and the evidence-quality score that sets sizehanko/decision/policy.py risk limits, hashed into every recordhanko/decision/engine.py the verdict function -- pure by contracthanko/decision/record.py the record, and the commitment that names ithanko/decision/ledger.py append-only ledger, and the replay proofhanko decide x --token TOKENA --subject voice_alpha --subject voice_beta --subject voice_gamma --market fixtures/market_tokena.json --as-of 2026-08-27T12:00:00Z --fixture fixtures/x_three_voices.jsonENTER TOKENA size 3.28% confidence 0.66 dec_1c1fb9e7ae2020cb260d6f32 evidence quality 0.82 (completeness 1.0, freshness 0.75, corroboration 1.0, independence 0.67) + independent_voices: 2 independent voice(s): voice_alpha, voice_gamma + safety: safety score 0.82 ~ echo voice_beta: marked as a repost or quote by the source ! wrong if price_usd < 1.0625 at any point within 72.0h (thesis fails if price falls 15% from entry) ! wrong if independent_voices < 2.0 at review, within 72.0h (entry rested on convergence that no longer holds) review at 2026-08-30T12:00:00Z
replayed from stored bytes: same decision idhanko review --observations fixtures/observations_day3.json --now 2026-08-30T12:00:00ZFALSIFIED TOKENA (enter at confidence 0.66) dec_1c1fb9e7ae2020cb260d6f32 -> rev_24903844c6020591a568451b x price_usd observed at 1.02 at 2026-08-30T12:00:00Z; committed to being wrong if < 1.0625 at any point in the window -- thesis fails if price falls 15% from entry + liquidity_usd held against < 630000.0 across 1 sample at 2026-08-30T12:00:00Z -- no intermediate readings; last observed 880000.0 + independent_voices observed at 2.0; holds against < 2.0 realised return -18.4% (recorded, not used to grade)hanko scorecardreviewed 2 scored 2 unverifiable 0held 1 falsified 1 hit rate 50.0% brier 0.2461
calibration said actual n 0.6-0.8 0.7 50.0% 2
voices voice_gamma 0.0% 1 scored voice_alpha 50.0% 2 scored
rules satisfied on decisions that later independent_voices 0.0% held conviction 50.0% heldhanko sweep --watchlist watchlist.json --as-of 2026-08-27T12:00:00Zhanko seal --watchlist watchlist.live.json --ledger live/decisions.jsonl --reviews live/reviews.jsonl --samples live/samples.jsonl --manifest-dir live/runs --interpreter lexicon --lookback-hours 24 --otshanko live-summary --dir livehanko sweep --watchlist fixtures/sweep_demo/watchlist.json \ --fixture-dir fixtures/sweep_demo --as-of 2026-08-27T12:00:00Zsweep at 2026-08-27T12:00:00+00:00 ENTER TOKENA dec_5b2eadbf21bc8c073927b4ac