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 deciqAI/knowledge-skills --skill bullseye-traction-channelsgit clone --depth 1 https://github.com/deciqAI/knowledge-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/deciqai/knowledge-skills/bullseye-traction-channels)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/bullseye-traction-channels"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/bullseye-traction-channels/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/deciqai/knowledge-skills/bullseye-traction-channels"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/bullseye-traction-channels.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 | $0.00087 | $0.00678 |
| Opus 5 | $0.00044 | $0.00339 |
| Sonnet 5 | $0.00017 | $0.00136 |
| Haiku 4.5 | $0.00009 | $0.00068 |
Grade A, and why
bullseye-traction-channels 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bullseye — Find the One Traction Channel That Works
Overview
From Traction (Weinberg & Mares, 2014): most startups die from lack of distribution, not product, and they fail because they over-invest in one favored channel instead of systematically testing across all of them. The Bullseye framework cycles through 19 traction channels (SEO, content, paid, virality, sales, partnerships, community, PR, events, etc.), runs cheap tests, and concentrates on the one channel that is currently working.
When to Use
- No repeatable customer-acquisition channel yet
- Effort sunk into one channel out of habit/comfort
- Reallocating a limited growth budget
The Process
- Brainstorm all 19 channels — a realistic idea for each, including ones you'd dismiss. Gate: skipping "unlikely" channels is how you miss the one that works.
- Rank into three rings: inner (promising now), middle (possible), outer (long shots).
- Run cheap parallel tests on the inner ring — small, time-boxed, with a target CAC/response bar defined up front.
- Read the data, not your preference — which test hit the bar?
- Pick one channel and focus — double down on the single working channel; ignore the rest for now. Gate: spreading across 3+ channels pre-fit = none get enough to work.
- Re-run when the channel saturates — channels decay; cycle Bullseye again.
Applying It Well
- Test to a pre-set success bar so results are decisive, not vibes.
- One working channel is usually enough to reach the next stage.
- Founder bias toward a comfortable channel is the most common failure.
Red Flags
- Committing to a channel before testing it.
- "Doing a bit of everything" and nothing at scale.
- No CAC/response threshold set before the test.
Verification
- All 19 channels considered, ranked into three rings
- Inner-ring tests run with a pre-set success bar
- Decision made on data, not preference
- Focus concentrated on the single working channel
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.
- 12d ago First seen · 44 lines · 87 tokens per session scan A 355dcb5fa8b2
bullseye-traction-channels is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 87 tokens to every session and 678 once invoked, about $0.0004 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.
Other skills, from other repositories
edge-tts
Text-to-speech conversion using uvx edge-tts for generating audio from text. Use when (1) User requests audio/voice output with the "tts" trigger or keyword. (2) Content needs to be spoken rather than read (multitasking, accessibility, driving, cooking). (3) User wants a specific voice, speed, pitch, or format for TTS…
mcp-deepwiki
Skills for accessing and searching docs in DeepWiki/GitHub’s public code repositories can help users understand open-source project source codes, and users can also ask questions directly about the code docs.
tianqi
A weather-lookup workflow for Chinese locations, covering forecasts, hourly conditions, weather warnings, and daily-life indexes.
compliance-check
Compliance pre-flight for a feature, campaign, or initiative — maps the data and activity involved, checks applicable regimes (privacy/GDPR-style, consumer protection, marketing rules, sector-specific), lists required approvals and notices, builds a gap list with remediation owners, and ends in a go/no-go…
plan-payroll
Plans payroll cash: true loaded cost per hire (gross plus employer taxes, benefits, tools), a payroll calendar with cutoffs and cash-out dates, a scenario table for new hire vs raise vs contractor-vs-employee, and a payroll-to-revenue check against rough industry bands. Use when the user asks "can I afford to hire"…
ui-ux-pro-max
Builds an end-to-end UI system for a product — design tokens (color scale, type scale, spacing, radii, shadows), a component inventory covering every interaction state, a layout grid, and WCAG contrast checks — emitted as CSS variables plus a component spec doc. Use when the user says "set up a design system", "create…