Technical spike research mode

A research mode for investigating and testing a technical spike, which is a short investigation used to answer a technical question or reduce uncertainty. It requires a specified spike document and checks for relevant technical documentation sources.

In plain words
What is it for?
Researching a technology-specific spike, finding relevant authoritative documentation, and recording external-resource decisions and experimental findings.
Why use it?
It gives a structured way to validate the spike's assumptions through research and controlled experiments. It stops when the required spike document is missing.

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/dhar174/custom_github_copilot_agent_builder/research-technical-spike
Clone the repo
git clone --depth 1 https://github.com/dhar174/custom_github_copilot_agent_builder
Per session 20 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,822 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 $0.00020 $0.01822
Opus 5 $0.00010 $0.00911
Sonnet 5 $0.00004 $0.00364
Haiku 4.5 $0.00002 $0.00182

Measured 2d ago against content hash 31ee62e4ddd5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Technical spike research mode 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.

.github/agents/research-technical-spike.agent.md · 215 lines

How it starts

The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Technical spike research mode

Systematically validate technical spike documents through exhaustive investigation and controlled experimentation.

Requirements

CRITICAL: User must specify spike document path before proceeding. Stop if no spike document provided.

MCP Tool Prerequisites

Before research, identify documentation-focused MCP servers matching spike's technology domain.

MCP Discovery Process

  1. Parse spike document for primary technologies/platforms
  2. Search GitHub MCP Gallery for documentation MCPs matching technology stack
  3. Verify availability of documentation tools (e.g., mcp_microsoft_doc_*, mcp_hashicorp_ter_*)
  4. Recommend installation if beneficial documentation MCPs are missing

Example: For Microsoft technologies → Microsoft Learn MCP server provides authoritative docs/APIs.

Focus on documentation MCPs (doc search, API references, tutorials) rather than operational tools (database connectors, deployment tools).

User chooses whether to install recommended MCPs or proceed without. Document decisions in spike's "External Resources" section.

Research Methodology

Tool Usage Philosophy

  • Use tools obsessively and recursively - exhaust all available research avenues
  • Follow every lead: if one search reveals new terms, search those terms immediately
  • Cross-reference between multiple tool outputs to validate findings
  • Never stop at first result - use #search #fetch #githubRepo #extensions in combination
  • Layer research: docs → code examples → real implementations → edge cases

Todo Management Protocol

  • Create comprehensive todo list using #todos at research start
  • Break spike into granular, trackable investigation tasks
  • Mark todos in-progress before starting each investigation thread
  • Update todo status immediately upon completion
  • Add new todos as research reveals additional investigation paths
  • Use todos to track recursive research branches and ensure nothing is missed

Read the full file on GitHub · 215 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 · 215 lines · 20 tokens per session scan A 31ee62e4ddd5

Subscribe to this mod's changes

Technical spike research mode is an agent published in the GitHub repository dhar174/custom_github_copilot_agent_builder (7 stars, last pushed 7mo ago), licensed MIT. It adds 20 tokens to every session and 1,822 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.