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In Edy Cu’s test sample of 11 tokens, buyers tagged as professional cohorts accounted for 0–3.6% of decentralized-exchange (DEX) buy volume. That is a result from one author’s limited set of observations—not evidence that professionals always make up less than 4% of token buying. The more noticeable effect on Cu’s sell schedules came from observed Smart Money and exchange flows.
Cu built Glidepath to help pace a token sale: enter a token, chain, and amount held, and it produces a dated calendar with one tranche per day. It is a planning tool, not a trading service. Read Cu’s account on DEV Community.
What Glidepath does—and what it does not do
Glidepath turns a token holding into a proposed selling calendar. The user provides the token, blockchain, and amount held; the tool estimates daily sale tranches and generates an .ics calendar file. Cu describes its boundary plainly: “It plans. It never trades.”
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That distinction matters. A schedule is not an order, does not execute swaps, and cannot guarantee a price or reduce market impact. The calendar is a pacing suggestion based on available data and assumptions; conditions can change before any scheduled sale.
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What “under 4%” means in Cu’s sample
Cu reports that labeled professional buyers contributed 0–3.6% of DEX buy volume across 11 tested tokens. Within that same reported sample, major tokens were 98.5–100% organic by the tool’s classification, while fresh Solana launches were 96.4–96.7% organic. Four sniper-bot labels matched no rows in the observations described.
These percentages reflect Cu’s chosen tokens, measurement window, and Nansen classifications. They are not a market-wide statistic, and “organic” here means buying not attributed to the labeled professional cohorts—not a verified judgment about a wallet owner’s motives or identity.
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How the buyer labels are counted
Cu says Glidepath queries Nansen’s tgm/who-bought-sold endpoint with include and exclude filters for smart-money labels. In eight token probes, he reports that the two filtered sets partitioned the buyer set exactly. He also notes that the returned address_label is a display name; it does not show which specific filter label caused an address to match.
Rather than page through every unlabeled buyer, the implementation takes total DEX buys from Nansen’s tgm/token-information endpoint and subtracts the buy volume attributed to labeled buyers. Cu says professional-buyer lists in his observations contained no more than 67 wallets, while a seven-day query for young Solana launches showed more than 20,000 buying addresses and was still truncated after 20 pages. That makes the subtraction approach practical for his design, but it also means the estimate inherits the coverage and classification limits of the underlying endpoints.
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How Glidepath turns flows into a selling calendar
Estimate daily organic buying
The planner estimates seven-day organic DEX buy volume by subtracting labeled professional-buyer volume from total DEX buys. It then divides that estimate by seven to produce an average daily figure. In Cu’s PEPE snapshot, recorded September 16, 2026, total DEX buys over seven days were $3,236,056; $24,893 was attributed to labeled cohorts. The tool counted 528 organic buyers and estimated organic buys of $458,738 per day.
Adjust for observed flow risk
Glidepath also uses current-day tgm/flow-intelligence data and flow history from the preceding 13 complete days via tgm/flows. It marks a day red when Smart Money net selling exceeds a threshold or exchange deposits exceed a threshold tied to estimated organic daily buys. Cu says the current-day Smart Money cohort uses the smart_trader definition, while historical flow uses smart_money; in the PEPE example those definitions corresponded to 21 wallets and 18 holders, respectively.
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A red current day halves the first tranche. The rate of red days in the recent history stretches the expected completion date. In the PEPE history Cu describes, four of 13 days were red, alongside exchange deposits ranging from +$499,000 to +$1.92 million. In a later PEPE demonstration, +$736,000 in net exchange deposits coincided with a halved first tranche.
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Set the tranche size
The proposed daily tranche is the smaller of a risk-adjusted share of estimated organic daily buys and 1% of reported liquidity. The share declines from 10% to 3% as Nansen peer-percentile risk indicators rise. This is a rule for generating the calendar, not evidence that a particular tranche will execute at the estimated cost or avoid moving the market.
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What the PEPE example says about pacing
For the PEPE example, Cu reports two tranches of $30,598 and $9,372. Under Glidepath’s constant-product cost approximation, the estimated cost was $147.90 for the paced sales versus $230.36 for selling the entire holding at once. Those are the author’s model outputs, not independently reproduced execution results or a promise of savings in live trades.
The tool cannot know whether future days will be red or green. A future calendar entry therefore needs a fresh check on its scheduled day; a planned tranche is not a forecast that market conditions will remain favorable.
Important limits before relying on a plan
- Approximate liquidity model: The cost calculation treats
liquidity_usdas a single pool with the token on one side. Cu warns that this can overstate depth when liquidity is concentrated in a thin pool. - Costs not included: The estimate excludes MEV and gas. Cu says only Solana and Base receive a real routed quote; other chains should not be read as having the same quote quality.
- Label and flow definitions: Cohort results depend on Nansen’s labels and endpoints. A display name alone does not reveal the matched filter label, and the current-day and historical Smart Money definitions differ.
- Stablecoin coverage: The described implementation has no history strip for stablecoins because the relevant endpoint returns a 422 error.
- API usage: Cu reports that even a valid but nonexistent address consumes 12 credits.
Cu also reports six property-test properties run 10,000 times each, 258 Vitest tests, 13 recorded plans replayed byte-for-byte offline, and live cold-plan latency of p50 3.5 seconds and p95 6.0 seconds. These are developer-reported checks and timings; they have not been independently verified.
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Glidepath is aimed at someone who already holds a token and wants a structured way to consider spreading a sale over time rather than selling all at once. Its visible inputs and calendar can make the pacing assumptions easier to inspect, but the result remains dependent on third-party data, the selected labels, liquidity assumptions, and conditions at execution time.
Cu calls it “a pacing calculator with its reasoning shown” and says, “This is not financial advice.” It should be treated accordingly: as a planning aid, not an execution service, market-impact guarantee, or recommendation to buy or sell any asset.
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