research-channel

research-channel is a skill for Claude Code, Codex from forsvn-labs/meta-skills. It costs 49 tokens per session (407 once invoked), scanned A, original, MIT.

A research process for choosing a marketing channel, such as search, social media, email, or advertising, based on audience fit, evidence, platform rules, content formats, and available capacity. A marketing channel is a place or method used to reach potential customers.

In plain words
What is it for?
Use it to compare candidate channels, audit existing performance, choose formats and audiences, identify proof and measurement needs, and decide how to run the channel.
Why use it?
It helps avoid choosing channels because they are popular or because of generic best practices. It compares what has actually worked, what the platform currently allows, and what the team can realistically produce.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the conquistador plugin — 21 skills shipped together

Good fit Use it to compare candidate channels, audit existing performance, choose formats and audiences, identify proof and measurement needs, and decide how to run the channel.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/forsvn-labs/meta-skills/research-channel
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.

Any agent
npx skills add forsvn-labs/meta-skills --skill research-channel
Clone the repo
git clone --depth 1 https://github.com/forsvn-labs/meta-skills

Made for: Claude Code, Codex.

Or install conquistador, the plugin that ships this one along with the rest of its 21 skills.

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 research-channel

README.md
[![agentmods](https://agentmods.dev/badge/skills/forsvn-labs/meta-skills/research-channel/github.svg)](https://agentmods.dev/skills/forsvn-labs/meta-skills/research-channel)
Your own site
<a href="https://agentmods.dev/skills/forsvn-labs/meta-skills/research-channel"><img src="https://agentmods.dev/badge/skills/forsvn-labs/meta-skills/research-channel/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.

agentmods 80×15 button for research-channel

Your own site · 80×15
<a href="https://agentmods.dev/skills/forsvn-labs/meta-skills/research-channel"><img src="https://agentmods.dev/badge/skills/forsvn-labs/meta-skills/research-channel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 407 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00049 $0.00407
Opus 5 $0.00024 $0.00204
Sonnet 5 $0.00010 $0.00081
Haiku 4.5 $0.00005 $0.00041

Measured 13d ago against content hash 521c6c874575, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-13, from the pricing page.

Security

Grade A, and why

research-channel 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 13d 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.

skills/research-channel/SKILL.md · 64 lines

What it actually says

Research a channel decision

Choose where and how to operate from evidence, fit, and capacity—not popularity.

Define the decision

Name the product, audience, outcome, candidate channels, time horizon, operator capacity, and what would change the choice. A channel audit without a decision becomes a fact dump.

Keep evidence types separate

Collect and label:

  • owned/account performance with source, window, sample, and comparable format;
  • operator-supplied experience and constraints;
  • current primary platform documentation and policy;
  • current observed examples or manual sampling;
  • third-party benchmarks with population and comparability;
  • inference and unknowns.

Use freshness appropriate to the claim. Reverify volatile formats, ranking signals, policy, pricing, and platform features at execution time. Owned results can guide account-specific choices without overriding brand, safety, or channel-fit floors.

Compare fit

For each channel assess:

  • audience habitat and intent;
  • native format and value delivered in-channel;
  • proof available;
  • distribution/access advantage;
  • feedback speed;
  • production and participation capacity;
  • destination readiness;
  • safety, policy, and reputation risk;
  • primary outcome and realistic diagnostics.

Include a veto: when the product should not use the channel.

Deliver

Return:

  1. decision and evidence boundary;
  2. owned-evidence readout;
  3. public evidence with source/freshness notes;
  4. focused channel comparison;
  5. recommended channel, role, format, and first test;
  6. channels to defer and why;
  7. next evidence and revisit date.

Do not publish, contact communities, access private analytics, or change live channel settings without explicit approval.

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 13d ago First seen · 64 lines · 49 tokens per session scan A 521c6c874575

Subscribe to this mod's changes

research-channel is a skill published in the GitHub repository forsvn-labs/meta-skills (14 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 407 once invoked, about $0.0002 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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