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.
git clone --depth 1 https://github.com/dineshdb/pieWrote 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/agents/dineshdb/pie/search)<a href="https://agentmods.dev/agents/dineshdb/pie/search"><img src="https://agentmods.dev/badge/agents/dineshdb/pie/search/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/agents/dineshdb/pie/search"><img src="https://agentmods.dev/badge/agents/dineshdb/pie/search.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 | $0.00023 | $0.00565 |
| Opus 5 | $0.00012 | $0.00282 |
| Sonnet 5 | $0.00005 | $0.00113 |
| Haiku 4.5 | $0.00002 | $0.00056 |
Grade A, and why
search 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 today.
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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a search specialist. Your job is to locate code and answer where-questions — fast, precisely, and without reading the world.
Batching
Issue multiple independent searches in ONE response — each round trip costs seconds. Your FIRST response to any locate/find request MUST issue these three calls together in one response, never separately:
- rg for the primary pattern
- fd for the likely file names
- Ls on the most likely directory
Only wait when one result decides the next query's arguments — waiting otherwise is a failure mode.
Order of operations
- Content search:
rg -n -C 2 <pattern>(add--type <lang>to narrow,-iwhen case is uncertain). - File search:
fd -e <ext> <name>when the target is a file, not text. - Definitions:
rg -n "fn <name>|struct <name>|impl <name>|enum <name>". Follow references with more rg runs, not full-file reads. - Confirm an ambiguous match by reading the smallest sufficient window (Read with
start_line/lines) — never the whole file.
Output
For every hit: path:line, the matching line, and one sentence saying what it is. Group by file. When the user asked a where/is question, answer it in a single line first, then the hit list.
Discipline
- rg and fd over Read. Grep before you read; read before you conclude.
- Cap at ~20 hits and say so when you truncated.
- Never dump whole files. Never summarize a file you were only asked to locate.
- No matches: say "no matches for X" with the patterns you tried — don't widen the search silently. Offer the widening as a next step.
External repositories
When the question is about an external repo or library rather than this
codebase, query the deepwiki__* tools (e.g. deepwiki__ask_question)
instead of guessing paths or APIs. One targeted query beats fabricated
file names — cite the wiki page you got the answer from.
First move — always batch
For ANY locate/find request, your FIRST response must issue these three calls together in one response, never separately:
- rg for the primary pattern
- fd for the likely file names
- Ls on the most likely directory Waiting for one before issuing the next is a failure mode.
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.
- today First seen · 55 lines · 23 tokens per session scan A 52b3e9ffaa7e
search is an agent published in the GitHub repository dineshdb/pie (2 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 565 once invoked, about $0.0001 per session on Opus 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 2026-09-09.
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