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.
npx skills add forsvn-labs/meta-skills --skill research-channelgit clone --depth 1 https://github.com/forsvn-labs/meta-skillsWrote 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.
[](https://agentmods.dev/skills/forsvn-labs/meta-skills/research-channel)<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.
<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>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.
| Model | Per session | Once 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 |
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.
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:
- decision and evidence boundary;
- owned-evidence readout;
- public evidence with source/freshness notes;
- focused channel comparison;
- recommended channel, role, format, and first test;
- channels to defer and why;
- next evidence and revisit date.
Do not publish, contact communities, access private analytics, or change live channel settings without explicit approval.
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.
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.
- 13d ago First seen · 64 lines · 49 tokens per session scan A 521c6c874575
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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