research

Guidance for combining findings from web and GitHub research. It is used internally by planning and bug-investigation agents when research files are available.

In plain words
What is it for?
Use it to identify the main findings, practical patterns, warnings, debugging references, and the evidence that most affects a recommendation.
Why use it?
It helps turn scattered research into an evidence-aware answer instead of treating every source as equally reliable.

Skill for Claude CodeCodex

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 skills/romiluz13/cc10x/research
Any agent
npx skills add romiluz13/cc10x --skill research
Clone the repo
git clone --depth 1 https://github.com/romiluz13/cc10x

Made for: Claude Code, Codex.

Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,231 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 $0.00026 $0.01231
Opus 5 $0.00013 $0.00616
Sonnet 5 $0.00005 $0.00246
Haiku 4.5 $0.00003 $0.00123

Measured 2d ago against content hash 25b1d0acaaa3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

research 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.

plugins/cc10x/skills/research/SKILL.md · 116 lines

How it starts

The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Synthesis Guidance

Overview

This skill is loaded via SKILL_HINTS by cc10x:planner and cc10x:bug-investigator when the router passes research files in the prompt. It provides instructions for synthesizing web and GitHub research findings.

This skill does NOT execute research. Research execution is done by:

  • cc10x:researcher (web mode) — prefers Bright Data, falls back to WebSearch/WebFetch
  • cc10x:researcher (github mode) — prefers Octocode MCP, falls back to package/docs/GitHub web research

Synthesis Goal

After the router passes research file paths in your prompt, read the available files and produce a synthesis that:

  1. Answers the knowledge gap (the Reason field from your prompt)
  2. Identifies the top 2-3 actionable patterns
  3. Lists gotchas with solutions
  4. Provides specific references for debugging
  5. Reflects evidence quality honestly
  6. States the single finding that most changed the recommendation

What Makes Good Synthesis

Include:

  • Cross-source confirmation (when web + GitHub agree on a pattern, it's reliable)
  • Primary-source preference: prefer the source that owns the claim — spec, first-party docs, shipped code. A secondary write-up citing a primary loses to the primary.
  • Conflict resolution: when sources disagree, code-backed, cross-confirmed findings override single-source prose; shipped code overrides docs (docs describe intent; code is what runs). Partial matches (one strong source only) require adaptation — state the adaptation rationale explicitly.
  • Confidence calibration from the router-provided ## Research Quality block
  • Gotchas the user probably hasn't considered
  • Specific code snippets only when they materially change the recommendation

Exclude:

  • Raw dump of all findings (summarize)
  • Obvious things the AI already knows
  • Findings not relevant to the specific Reason for research

Same-Name Disambiguation

A name (package, repo, handle) is not a unique key. Researchers routinely retrieve content where one name collides across distinct entities — two npm packages publish under the same name, the same handle exists on two platforms run by different people, a repo name is forked or squatted under multiple owners. This is retrieval noise, not a source conflict.

Read the full file on GitHub · 116 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 · 116 lines · 26 tokens per session scan A 25b1d0acaaa3

Subscribe to this mod's changes

research is a skill published in the GitHub repository romiluz13/cc10x (164 stars, last pushed 29d ago), licensed MIT. It adds 26 tokens to every session and 1,231 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 2026-08-30.

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