Letter to Day-One-Me: Three Mistakes That Ate My First Day on a Free Endpoint

Dear day-one me,

You will start at 09:10 with a free model endpoint and a free server.
You will finish at 21:40 with one merged pull request and no idea why.
That gap is not bad luck. It is three missing measurements.

I am writing down the fixes so you skip the twelve hours.

The day, as it actually went

Hour one: you paste a 400-line file and wait for a timeout.
Hour two: you assume the server is down and restart it twice.
Hour four: the output looks fine, so you trust it and ship a broken import.
Hour seven: you are debugging a bug you introduced by trusting exit 0.
Hour nine: you finally measure something. Cold start was 41 seconds, not 4.

The rest of the day was cleanup. Here is the corrected order of work.

Mistake 1 — You prompted before you measured the box

A free server is not a laptop. Cold start is real. Network hops are real.
You cannot budget what you never timed.

Write a preflight probe first. It runs in two seconds and saves hours.
This template is unexecuted. Point it at your own endpoint URL.

#!/usr/bin/env python3
"""preflight.py - measure before you prompt. Template, not a benchmark."""
import json, os, socket, time, urllib.request

ENDPOINT = os.environ["MC_ENDPOINT"]  # e.g. https://your-free-server.example

def http_probe(url, timeout=8.0):
    t0 = time.perf_counter()
    status = None
    try:
        with urllib.request.urlopen(url, timeout=timeout) as r:
            status = r.status
    except Exception as exc:
        status = type(exc).__name__
    return {"check": "http", "url": url, "status": status,
            "ms": round((time.perf_counter() - t0) * 1000, 1)}

def tcp_probe(host, port, timeout=3.0):
    s = socket.socket()
    s.settimeout(timeout)
    t0 = time.perf_counter()
    ok = False
    try:
        s.connect((host, port))
        ok = True
    except OSError:
        ok = False
    finally:
        s.close()
    return {"check": "tcp", "target": f"{host}:{port}", "open": ok,
            "ms": round((time.perf_counter() - t0) * 1000, 1)}

def cold_start(url, rounds=3):
    # Second hit should be faster if the box keeps a warm process.
    samples = [http_probe(url)["ms"] for _ in range(rounds)]
    return {"check": "cold_start", "samples_ms": samples,
            "first_minus_rest_ms": round(samples[0] - min(samples[1:]), 1)}

receipt = {"endpoint": ENDPOINT, "results": [
    http_probe(ENDPOINT),
    cold_start(ENDPOINT),
]}
print(json.dumps(receipt, indent=2))

Run it three times. Compare the first sample to the rest.
If the gap exceeds your timeout budget, raise the timeout. Do not restart the server.

Mistake 2 — You had no ledger, so you had no budget

Free model access is finite. You cannot see a limit you never count.
Day-one you spent the allowance on retries, not on work.

The fix is a counter that aborts before the request, not after.
This is a sketch, not a library. Ten lines is enough.

import json, time

class Ledger:
    def __init__(self, path, cap_tokens):
        self.path, self.cap = path, cap_tokens
        self.used = 0

    def charge(self, prompt_tokens, completion_tokens):
        cost = prompt_tokens + completion_tokens
        if self.used + cost > self.cap:
            raise RuntimeError(f"budget stop: {self.used}+{cost} > {self.cap}")
        self.used += cost
        with open(self.path, "a") as f:
            f.write(json.dumps({"ts": time.time(), "used": self.used}) + "\n")
        return self.used

Rules that worked for me:

1. Set the cap at half your expected allowance. Retries eat the rest.
2. Log every attempt, including the failed ones. Failures cost tokens too.
3. Stop the loop on RuntimeError. Never catch it and continue.
4. Print remaining budget every ten calls. Silence hides drift.

Mistake 3 — You trusted exit code 0

Generated code that runs is not generated code that is correct.
Day-one me merged a patch that exited clean and broke a schema.

Gate the output before it touches a branch. Check three things only.
Does it parse? Does it match the expected shape? Does it stay inside the sandbox?

# 1. Parse gate: fail fast on invalid syntax
python -m py_compile ./agent_out/*.py

# 2. Shape gate: assert the contract, not the vibe
python - <<'PY'
import json, sys
payload = json.load(open("agent_out/result.json"))
required = {"files", "tests_passed", "notes"}
missing = required - payload.keys()
if missing:
    sys.exit(f"shape gate failed: missing {sorted(missing)}")
print("shape gate ok")
PY

# 3. Isolation gate: never run agent output on the host
# Use the free server / container, not your laptop shell.

That third gate is the one that matters most. The free server exists for this.
Run the agent there. Keep your local machine clean.

Why this project fits the loop

MonkeyCode is an open-source coding agent project. The operator states it offers free model access and a free server option. Check the repo for current terms; availability changes.

Disclosure: This article was prepared as part of MonkeyCode's product outreach.

Two things made it useful for this exact workflow. First, free model access meant I could run the ledger drill without a billing surprise. Second, the free server gave me a place to run untrusted output that was not my laptop. The project advertises a 10M-token free allowance at the time of writing. Verify that number yourself before you plan around it.

What it did not do: it did not fix my ordering. The tool was fine on day one. My sequence was wrong.

The corrected first hour

Do this in order. It takes about twenty minutes.

1. Clone the repo and read the setup section once, fully, before typing.
2. Run preflight.py against the free server. Record cold start.
3. Set the ledger cap. Write it in the repo, not in your head.
4. Build the three gates as a single script named gate.sh.
5. Point the agent at one small file. Not the 400-line one.
6. Confirm the receipt, the ledger line, and the gate output all exist.
7. Only then scale up the task size.

When to use the free server, and when not to

Situation	Free server	Local shell
Untrusted generated code	Yes	No
Cold start under 5s needed	Measure first	Yes
Secrets in the environment	No	Vault only
Large local repo, many files	Partial clone	Yes
Long batch runs	Budget the ledger	Yes
Reproducible CI parity	Good fit	Good fit

Read the first row twice. That row is the whole reason to bother.

Limitations and who should skip this

This workflow does not make a free tier production-grade. It makes it measurable.
If you need hard latency SLOs, a free shared server is the wrong tool.
If your code handles regulated data, do not send it anywhere without review.
If you cannot verify current quotas yourself, do not build a plan on them.

Skip this if you already have a sandbox and a metered budget. You solved it.

What I would tell you at 09:10

Measure the box. Count the tokens. Gate the exit code. In that order.
The tool was never the problem. The missing receipts were.

If you want to run the same drill, the project is open source and the free tier lets you practice the ordering before you pay for anything. Start with preflight.py, not with a prompt.

— me, twelve hours later