Terse Replies With Technical Precision
Get concise answers that preserve critical details, exact code, uncertainty, and next actions, with optional caveman mode.
Before & after
Same prompt, same agent — the only difference is the skill.
API rate limiting is an important concept to understand for building resilient systems. When an API provider sets rate limits, they're trying to prevent any single client from overwhelming their servers with too many requests. Different APIs have different limits, which are usually measured in requests per second or requests per day. To handle rate limiting in production, you need to implement backoff strategies. The most common approach is exponential backoff, where you wait progressively longer between retry attempts. For example, you might wait 1 second after the first failed request, 2 seconds after the second, 4 seconds after the third, and so on. You should also respect the Retry-After header if the API provides one. Another consideration is request queuing. Instead of firing all requests at once, you can use a queue to space them out over time. This is especially important if you're processing large batches of data. You might also want to implement circuit breakers, which automatically stop sending requests to an API if it's returning too many errors.
API RATE LIMITING - PRODUCTION NOTES
What it is: Server says "hold on, you're hitting me too fast." Response: Wait, then retry.
How to handle:
1. Exponential Backoff
Try #1 → Wait 1s → Try #2 → Wait 2s → Try #3 → Wait 4s
Cap: Don't exceed 60s per retry
2. Respect Retry-After Header
Server says "retry in 120s" → You wait 120s, not your own math
3. Queue Requests
Don't fire 1000 requests at once. Drip them: 10/second max.
4. Circuit Breaker
If 10 consecutive failures → Stop. Wait 5 min. Try once. If fail, wait 5 min more.
Code shape (pseudocode):
function callWithBackoff(url, attempt=0) {
try { return fetch(url) }
catch error {
if (attempt > 5) throw error
wait(2^attempt seconds)
return callWithBackoff(url, attempt+1)
}
}
Trap: Never assume API limits are permanent. Monitor daily—they change. Log every 429 status to spot patterns.About this skill
“Just give me the answer” should not mean losing the condition that makes it correct. This skill trims preambles, repeated explanations, and unnecessary narration while protecting commands, uncertainty, exceptions, and next actions. Choose light brevity, terse replies, or full caveman-style fragments.
What it does
- Leads with the answer, fix, decision, or blocker instead of restating your request.
- Adjusts compression across three modes without shortening code or corrupting exact strings.
- Preserves negation, units, scope, prerequisites, and distinctions between completed and unverified work.
- Turns long troubleshooting replies into a likely cause, a targeted check, and a conditional fix.
- Reports tool results using the outcome, relevant evidence, and any remaining blocker.
- Checks whether compression changed the meaning before returning the shorter answer.
What you get
Shorter, task-sized replies with the information needed to act. Full caveman mode adds clipped phrasing where it remains understandable; no fixed token reduction, speed improvement, or cost savings are guaranteed.
Best for
Developers handling repeated small tasks, users watching usage limits, and anyone tired of reading paragraphs before reaching the answer.
SKILL.md preview
---
name: terse-replies-with-technical-precision
description: >-
Compress assistant replies by removing redundant narration and applying task-sized length budgets, then check that actions, conditions, uncertainty, and exact technical content survived. Offers light, terse, and full caveman modes. Use when the user says "stop explaining every step", "just give me the answer", "your replies are too long", "use fewer tokens", "talk like a caveman", "keep the technical details but cut the fluff", or "why do you keep repeating what I asked?"
---
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