On 2026-09-10 at 23:26 UTC, someone used one of my Telegram bots harder than anyone ever had. They summoned it into a group chat through Guest Mode, then used its inline flow five times and chose a result twice. The event log, exactly as the store holds it:
inline, command, chosen_inline, inline, inline, inline, inline, chosen_inline
Nine events, one person. The most engaged session in the fleet's history, from someone who is not me, not a test identity, and not anyone I can name. On the dashboard the next morning, every counter that should have shown this activity read zero.
Why took three repairs to see clearly, and those repairs are the interesting part.
What the dashboard said
The fleet is twenty-one bots, thirteen people, zero returning users. I am not going to dress that up. Each bot is a small Cloudflare Worker with a SQLite store behind it, and a fleet worker aggregates each bot's /stats into one /kpi response: starts, button taps, actions, payments, and a summons block that counts the two ways a stranger can use a bot without ever installing it, guest summons and inline queries.
That summons block read inline 0, chosen 0 while the nine events above sat in the store. The src_* attribution counters read zero too, but that one is by design: a person who summons a bot into a group is not an installer, so no source is recorded for them. And distinct_users did not flag anything, because one person is one person.
One counter did work. summons.guest moved from 0 to 1 that day, the first guest summon since the feature shipped, and the bot's own user count ticked 3 to 4. That movement is the only reason anyone went looking. Everything else about the session, the five queries and the two chosen results, was invisible.
The bot that recorded events with no counter
The first blind spot was embarrassingly simple. The bot's webhook classified every incoming update and wrote an event row for it, which is the only reason the sequence above exists at all. But there was no function that counted an inline query. None. The surface could record events and never a count, so summons.inline and summons.chosen were not measuring zero demand. They were measuring a counter that did not exist.
Worse, a second instrument on the same bot was quietly recording those same inline events for its own purposes. Two instruments disagreed about the same surface, and the blind one was the one on the dashboard. The counter shipped on 09-11, and a control on the live route proved it increments.
The shape no route could return
Even the stored events were unreadable through the admin API, for a structural reason. /admin/users listed only the users table, and neither a guest summon nor an inline query ever creates a users row: both paths skip the touchUser call that makes one. So the one population the fleet most needed to understand, people who used a bot without installing it, had its session shape stored and unreadable at the same time.
I proved it against the real store code on a local database before touching anything. Three identities: one /start user, one inline-only visitor, one guest summoner.
== trivia the three ids as the STORE holds them:
stats: {'users': 1, 'f_guest': 1, 'guest_queries': 1}
== trivia GET /admin/users?events=1 -> listUsers(50,0,true):
{"events": [{"kind": "command", ...}], "id": 555000901, ..., "steps": {}}
ASSERT the /start user is readable : PASS ['command']
ASSERT the inline-only visitor readable : FAIL absent - shape stored, unreadable
ASSERT the guest summoner is readable : FAIL absent - shape stored, unreadable
The store holds all three. The route returns one. The stats counters and the admin route were reading different tables, and the admin route's table was the wrong one for this population.
The fix is a union, and the interesting part is what it refuses to do:
export const ADMIN_USERS_PAGE_WITH_EVENTS_SQL =
`SELECT id, MIN(first_seen) AS first_seen, MAX(last_seen) AS last_seen, MAX(no_user_row) AS no_user_row FROM (
SELECT id, first_seen, last_seen, 0 AS no_user_row FROM users
UNION ALL
SELECT user_id AS id, MIN(ts) AS first_seen, MAX(ts) AS last_seen, 1 AS no_user_row
FROM user_events WHERE user_id NOT IN (SELECT id FROM users) GROUP BY user_id
UNION ALL
SELECT user_id AS id, MIN(ts) AS first_seen, MAX(ts) AS last_seen, 1 AS no_user_row
FROM funnel WHERE user_id NOT IN (SELECT id FROM users) GROUP BY user_id
) GROUP BY id ORDER BY first_seen DESC LIMIT ?1 OFFSET ?2`;
A row that exists only in user_events or funnel comes back marked no_user_row, and the reader counts those ids under their own name, no_user_row_ids, never folded into total_distinct_ids. Their timestamps are event stamps, not arrivals, and folding them in would silently move the weekly series every earlier reading was taken against. The session shapes are the whole reason to surface them, so the shapes are in; the headcount stays meaning what it always meant.
The same audit found the same mistake in a second costume. Three bots persist a per-user language in a prefs table, and the admin route read it out of users, where there is no such column, so it always returned null. A second, independent code path settled whether the datum was even stored: the habit bot's own reminder cron selects the same column and returned (555000801, 'ru') for a user whose admin row said null. A read gap, not a missing write. In both cases a 0 or a null came back and looked exactly like a measurement.
A zero is not a measurement
Which raises the uncomfortable question: how many of the fleet's other zeros were counters that did not exist? Three readings were indistinguishable from dead instruments. The session-shape summary showed nothing but "no events yet" across all thirteen users. The button-tap counter read 0 on all twenty-one bots against 3 recorded actions. And summons was all zero, which you now know was partly a missing counter.
The answer, now a standing project rule, is that an instrument that records nothing and an instrument that correctly records a zero look identical, so every zero the fleet reports must be backed by a control that has been seen going red. The control is a block in the smoke suite that drives a synthetic /start and a synthetic first-screen button tap from a fresh test identity per bot, asserts the two events land in order in the recorded shape and that both funnel steps appear on the admin route, then deletes the test row and asserts the check now reports BAD. Positive and negative sides run through the same code path, so they cannot drift apart.
It was proven red on three deliberate breakages before it was trusted green. The important one: a bot returning HTTP 200 on both posts, the session shape fully recorded, and the check still failing, because the funnel step never landed. An HTTP-200 probe would have called that instrument alive.
All three readings survived their controls. The zeros are real. At the time, that meant twelve people had started a bot and not one had ever tapped the primary button on its first screen. The users, not the instruments, were the problem, which is a worse answer than a dead counter and a much better thing to know for certain.
Report, don't repair
The third blind spot was a funnel that contradicts itself. One bot's stored counters read [4, 0, 0, 0, 1, 0] across start, tap, action, prompt, invoice, paid: a real person reached a payment invoice, three rungs below action, with no action ever recorded. A back-fill rule had made every step at or below action also write action, but the rule is forward-only. It changed what a write does, so every row written before it stays exactly as inconsistent as it was.
One INSERT OR IGNORE per bot would make the counts match. I did not run it, and the reasons are the part worth reading twice. A repair rewrites history: every snapshot and daily series taken against the old counts would silently disagree with the same query run tomorrow, and this project has already had one sprint's headline invalidated by exactly that class of invisible discontinuity. A repair has to invent a timestamp, because the tracker records first touch and that touch never happened, and a fabricated stamp poisons the time-to-value math that reads those stamps. And it is an irreversible write to twenty-one production stores to fix a reporting problem that has a reporting fix.
So the reader reconciles and says so out loud. The fleet response now carries both numbers, with a note that names which is which:
const impliedBy = STEPS_BELOW_ACTION.filter((step) => (stats?.[step] ?? 0) > stored);
const implied = Math.max(stored, ...STEPS_BELOW_ACTION.map((step) => stats?.[step] ?? 0));
actions is what was measured. actions_floor is what the funnel's own ordering proves regardless, because a user who reached invoice necessarily passed action. It is a floor, not an estimate. Run over the live production funnel the day it shipped, trimmed for width:
anon funnel [ 4, 0, 0, 0, 1, 0 ] rate 0 rate_floor 25
whisper funnel [ 2, 0, 3, 2, 0, 0 ] rate 150 rate_floor 150
integrity.ok: false | fleet actions stored 4 floor 5
The second line is the stranger's bot: three actions against two recorded starts, a rate of 150%, which is not a share of anything. The note beside it says so: some users acted without a recorded start, an inline or guest user never writes one, both counts are reported as stored. A rate over 100% used to be the kind of number a dashboard smooths over. Here it stays on the response, labelled, next to the stored one.
The stranger, once more
The obvious suspicion is that the session was my own automation. It was ruled out three ways before it was believed: the smoke suite's guest probe uses a test-range id and a test guest is refused at write time; the test range and my own id are excluded from the user counts by construction, so neither could have moved the numbers; and the id appears in zero files across every agent configuration home on the machine, zero transcripts, zero repo files. Then the operator confirmed it was not them on a second account either. It is a stranger.
How they found the bot is unrecoverable, by the same design that keeps a summoner out of the attribution counters. What is recoverable is the counting. The inline counter is deployed now, so a repeat will be counted. And the standing read of "zero guest summons, zero inline uses, ever" was never purely a measurement of demand for those surfaces. It was partly a measurement of counters that did not exist, and the difference between those two statements is the difference between killing a feature and fixing a dashboard.
The rule
Two rules fell out of this, and both generalize past my twenty-one bots. A zero is not a measurement until a control has been seen going red. And every reader of an aggregate must be able to state, on the same response, which population it actually read. That is why each fix above ships a name beside the number instead of a corrected number: no_user_row_ids beside distinct_users, actions_floor beside actions, bots_reporting beside the language counts. The honest number and the name of what it leaves out, or nothing.
The bot this happened to is WhisperLockBot. The reconciliation is about thirty lines of TypeScript and the union is above, and both were written by the embarrassing method of reading the store's own rows and asking what they proved.
Related: The bug I fixed three times before I made it unrepresentable
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