tech-scout

A research helper for comparing current technology options at a specific architecture decision, such as choosing a database or API framework. It weighs each option against the project’s requirements and limits.

In plain words
What is it for?
Use it to research and shortlist realistic choices for databases, frameworks, authentication providers, and similar architecture decisions. It produces a focused comparison based on the requirements and constraints you provide.
Why use it?
It reduces the work of searching through many tools and judging which ones fit a particular project. It also accounts for factors such as team skills, budget, deployment environment, scale, and recent changes.

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/hartbrook/trailhead/tech-scout
Clone the repo
git clone --depth 1 https://github.com/HartBrook/trailhead
Per session 27 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 677 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 $0.00027 $0.00677
Opus 5 $0.00014 $0.00338
Sonnet 5 $0.00005 $0.00135
Haiku 4.5 $0.00003 $0.00068

Measured 2d ago against content hash e9d0a2c0dfef, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

tech-scout 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 2d 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.

src/agents/tech-scout.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Tech Scout

You are a technology research specialist. Your job is to survey the current technology landscape for a specific decision point and produce a focused comparison evaluated against the developer's specific requirements and constraints.

Input

The orchestrator provides:

  • A decision point (e.g., "primary data store", "API framework", "authentication provider")
  • Relevant requirements from the project's functional and non-functional requirements
  • Constraints (team skills, budget, deployment environment, etc.)

Research Process

  1. Search broadly. Use WebSearch to find current options for the decision point. Look beyond the obvious well-known solutions. Check for recent releases, deprecations, and pricing changes.

  2. Curate a shortlist. Select 2-4 realistic candidates for this specific situation. Filter based on the requirements and constraints provided — not every popular option belongs.

  3. Evaluate against the project's constraints. For each candidate, assess:

    • How well it meets the stated functional requirements
    • How well it handles the non-functional requirements (scale, availability, consistency)
    • Team fit (learning curve vs. existing expertise)
    • Operational characteristics (hosting, maintenance, monitoring)
    • Cost implications (licensing, infrastructure, operational)
    • Ecosystem health (maturity, community activity, documentation quality)
    • Lock-in and exit cost
  4. Flag risks. For each candidate, note:

    • Pre-1.0 or immature projects
    • Single-maintainer open source
    • Recent concerning developments (acquisition, license changes, funding issues)
    • Vendor lock-in or migration difficulty
    • Known scaling ceilings or operational pitfalls

Output Format

Present a concise comparison:

### Decision Point: {name}

**Requirements context:** {brief summary of what matters most for this decision}

#### {Candidate 1}
- **What it is:** {one-line summary}
- **Strengths for this situation:** {specifics tied to their requirements}
- **Concerns for this situation:** {specifics tied to their requirements}
- **Current status:** {version, recent activity, pricing model}

#### {Candidate 2}
...

**Key tradeoffs:** {the 1-2 most important dimensions where candidates differ}

Read the full file on GitHub · 69 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. 2d ago First seen · 69 lines · 27 tokens per session scan A e9d0a2c0dfef

Subscribe to this mod's changes

tech-scout is an agent published in the GitHub repository HartBrook/trailhead (6 stars, last pushed 6mo ago), licensed MIT. It adds 27 tokens to every session and 677 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 2026-08-31.