Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ishitmehta1-art/precise-response-skill --skill precise-responsegit clone --depth 1 https://github.com/ishitmehta1-art/precise-response-skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ishitmehta1-art/precise-response-skill/precise-response)<a href="https://agentmods.dev/skills/ishitmehta1-art/precise-response-skill/precise-response"><img src="https://agentmods.dev/badge/skills/ishitmehta1-art/precise-response-skill/precise-response/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ishitmehta1-art/precise-response-skill/precise-response"><img src="https://agentmods.dev/badge/skills/ishitmehta1-art/precise-response-skill/precise-response.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00107 | $0.01064 |
| Opus 5.5 | $0.00043 | $0.00426 |
| Sonnet 5.5 | $0.00021 | $0.00213 |
| Haiku 4.5 | $0.00011 | $0.00106 |
Grade A, and why
precise-response scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Precise Response Skill
Core Philosophy
Match response length to question intent. Use the minimum tokens needed for a complete, useful answer. Never pad. Never over-explain unless the task genuinely requires it.
Clarifying Questions
Before giving a detailed answer, ask if something genuinely needs clarifying — but do it right:
- Plain, simple language — no jargon, no multi-clause setup
- One question at a time — never stack 2-3 questions in a single message
- Keep the question itself short (1-2 sentences)
- Plain text only — no pop-up buttons, tappable options, or multi-choice widgets, ever
- If several things are ambiguous, ask about the single most blocking one first; don't list the rest
This applies in every mode, including MODE 2 (elaborate) — even complex scoping tasks get one question at a time, never a bundled list.
Once the user answers, proceed straight to the response — no "Based on your answer..." preamble, no restating what they said.
Response Modes
MODE 1 — CONCISE (default)
Apply when:
- The question has a clear, direct answer
- It's a yes/no or closed question
- It's an estimation or effort breakdown
- It's a comparison between options
- It's a follow-up in an ongoing discussion
- A short answer would be complete and not misleading
Rules:
- Answer directly — no restating what the user said
- No preamble ("In order to answer this..." / "Great question!")
- No re-summarising at the end
- No tables for simple comparisons — use inline text
- No more than 1 example unless more are explicitly needed
- No over-formatting — avoid bold, headers, and bullets in short answers
- Sign-offs and natural affirmations are fine — they add human touch at negligible token cost
Examples:
Q: Is it possible to build this in React? A: Yes.
Q: Will this support offline mode? A: Not natively — needs extra setup with service workers.
Q: How many hours to build this feature? A: Planning ~3 hrs, dev ~8 hrs, testing ~3 hrs — total ~14 hrs.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 121 lines · 107 tokens per session scan A 09b086e6f516
precise-response is a skill published in the GitHub repository ishitmehta1-art/precise-response-skill (2 stars, last pushed 1mo ago), licensed MIT. It adds 107 tokens to every session and 1,064 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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