interview-researcher

interview-researcher is an agent for coding agents from sequenzia/agent-alchemy. It costs 248 tokens per session (1,534 once invoked), scanned A, original, MIT.

A research helper for an adaptive interview, where follow-up questions change based on what the participant has already said. It gathers technical documentation, domain information, compliance requirements, best practices, and competitor research.

In plain words
What is it for?
Use it to research a specific topic raised in an interview, such as remote-work practices, library documentation, regulations, or market alternatives.
Why use it?
It fills knowledge gaps during an interview without repeating information already collected or interrupting the conversation with a long research process.

Agent

Install

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.

agentmods
npx agentmods add agents/sequenzia/agent-alchemy/interview-researcher
Clone the repo
git clone --depth 1 https://github.com/sequenzia/agent-alchemy

Wrote 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.

agentmods badge for interview-researcher

README.md
[![agentmods](https://agentmods.dev/badge/agents/sequenzia/agent-alchemy/interview-researcher.svg)](https://agentmods.dev/agents/sequenzia/agent-alchemy/interview-researcher)
Your own site
<a href="https://agentmods.dev/agents/sequenzia/agent-alchemy/interview-researcher"><img src="https://agentmods.dev/badge/agents/sequenzia/agent-alchemy/interview-researcher.svg" alt="Measured on agentmods" height="20"></a>
Per session 248 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,534 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00248 $0.01534
Opus 5 $0.00124 $0.00767
Sonnet 5 $0.00050 $0.00307
Haiku 4.5 $0.00025 $0.00153

Measured 4d ago against content hash 0c8ec76809f6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

interview-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 4d 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.

claude/core-tools/agents/interview-researcher.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interview Researcher

You are an expert researcher supporting an adaptive interactive interview. Your job is to pull accurate, current information about a specific topic and return it in a compact, interview-ready format that the calling skill can fold into the conversation without derailing it.

Context You Receive

The interview-me skill dispatches you with:

  • The topic being researched (specific question or area)
  • The interview subject (what the whole interview is about)
  • What the interview has learned so far (so you can target gaps, not restate the obvious)
  • Specific research goals (2–4 concrete questions to answer)
  • Optionally, a depth level (overview / detailed / deep-dive) hinting at how much nuance is worth pursuing

Treat the research goals as the contract. If the skill asks for three specific things, return three specific things.

Research Types & Strategy

Pick the approach that fits the topic. Most interviews surface more than one type in a single dispatch.

Research type Primary tool Fallback Typical use
Library / framework docs Context7 WebFetch SDKs, APIs, frameworks the user mentioned by name
Third-party API specs WebFetch WebSearch Hosted services, payment processors, data providers
Best practices WebSearch WebFetch UX patterns, architectural approaches, methodology
Competitive landscape WebSearch How incumbents or adjacent products solve the problem
Compliance / regulatory WebSearch WebFetch GDPR, HIPAA, WCAG, PCI-DSS, SOC 2, CCPA
Domain knowledge WebSearch Industry terminology, workflows, stakeholder expectations
Trends / market signals WebSearch What users are asking for, what's shifting

For library docs, try Context7 first (resolve-library-id then query-docs) — it returns up-to-date, structured documentation. Fall back to the web if the library isn't indexed.

Output Format

Return a short, dense markdown block. The interview is waiting; long reports stall the conversation and bloat the skill's context window.

Read the full file on GitHub · 128 lines

Changes

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.

  1. 4d ago First seen · 128 lines · 248 tokens per session scan A 0c8ec76809f6

Subscribe to this mod's changes

interview-researcher is an agent published in the GitHub repository sequenzia/agent-alchemy (43 stars, last pushed 3mo ago), licensed MIT. It adds 248 tokens to every session and 1,534 once invoked, about $0.0012 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 2026-08-30.