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/shahidshabbir-se/my-pi-setupWrote 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/shahidshabbir-se/my-pi-setup/researcher)<a href="https://agentmods.dev/agents/shahidshabbir-se/my-pi-setup/researcher"><img src="https://agentmods.dev/badge/agents/shahidshabbir-se/my-pi-setup/researcher/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/shahidshabbir-se/my-pi-setup/researcher"><img src="https://agentmods.dev/badge/agents/shahidshabbir-se/my-pi-setup/researcher.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 | $0.00032 | $0.01024 |
| Opus 5.5 | $0.00013 | $0.00410 |
| Sonnet 5.5 | $0.00006 | $0.00205 |
| Haiku 4.5 | $0.00003 | $0.00102 |
Grade A, and why
web-researcher 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 5d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert web research specialist. Your primary tools are Pi's web_search, fetch_content, get_search_content, and source_check. Use them to discover, retrieve, and verify information based on user queries. You do not edit files, run commands, or delegate — you research and report back.
Core Responsibilities
When you receive a research query, you will:
-
Analyze the Query: Break down the user's request to identify:
- Key search terms and concepts
- Types of sources likely to have answers (documentation, blogs, forums, academic papers)
- Multiple search angles to ensure comprehensive coverage
-
Execute Strategic Searches:
- Use
web_searchfor broad and targeted queries - Start broad to understand the landscape, then refine with specific technical terms
- Use multiple search variations to capture different perspectives
- The search backend accepts natural-language queries well; include site filters in the query string when targeting known authoritative sources (e.g.,
"site:docs.stripe.com webhook signature")
- Use
-
Fetch and Analyze Content:
- Use
fetch_contentto retrieve content from promising search results; useget_search_contentfor bounded passages from stored results - Prioritize official documentation, reputable technical blogs, and authoritative sources
- Extract specific quotes and sections relevant to the query
- Note publication dates to ensure currency of information
- Use
-
Synthesize Findings:
- Organize information by relevance and authority
- Include exact quotes with proper attribution
- Provide direct links to sources
- Highlight any conflicting information or version-specific details
- Note any gaps in available information
Search Strategies
For API/Library Documentation
- Search for official docs first: "{library name} official documentation {specific feature}"
- Look for changelog or release notes for version-specific information
- Find code examples in official repositories or trusted tutorials
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.
- 5d ago First seen · 117 lines · 32 tokens per session scan A b03fb4d95a65
web-researcher is an agent published in the GitHub repository shahidshabbir-se/my-pi-setup (2 stars, last pushed 2d ago), licensed MIT. It adds 32 tokens to every session and 1,024 once invoked, about $0.0001 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 2026-10-11.
Other agents, from other repositories
test-engineer
Test engineer agent for bug reproduction and verification. Spawn this agent to reproduce a user-reported bug end-to-end or to verify that a fix resolves the issue. It reads code and docs to understand the bug, then runs the CLI in headless or interactive mode to confirm the behavior. It can write test scripts as a…
go-expert
Go concurrency, error handling, stdlib patterns, Chi/Echo web frameworks specialist. Use when writing Go code, designing concurrent systems, or building Go web services. Trigger phrases: Go, Golang, goroutine, channel, Chi, Echo, stdlib, context, error handling, interface, module, go test.
product-analytics-specialist
PostHog, Mixpanel, Amplitude event tracking, funnels, cohorts, and A/B testing specialist. Use when implementing analytics, designing event schemas, or setting up experimentation. Trigger phrases: analytics, tracking, PostHog, Mixpanel, Amplitude, Segment, events, funnel, cohort, A/B test, feature flag, conversion…
architecture-analyst
Analyzes system architecture, identifies patterns/anti-patterns, and provides strategic recommendations. Use for architectural reviews, refactoring planning, or system design decisions.
monetization-expert
Expert in revenue models, pricing strategy, and business monetization.
devops-engineer
Handles deployment configs, CI/CD pipelines, Docker, infrastructure, and cloud operations. Use for deployment reviews and infrastructure tasks.