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 synaptiai/synapti-marketplace --skill nci-analysisgit clone --depth 1 https://github.com/synaptiai/synapti-marketplaceWrote 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/synaptiai/synapti-marketplace/nci-analysis)<a href="https://agentmods.dev/skills/synaptiai/synapti-marketplace/nci-analysis"><img src="https://agentmods.dev/badge/skills/synaptiai/synapti-marketplace/nci-analysis/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/synaptiai/synapti-marketplace/nci-analysis"><img src="https://agentmods.dev/badge/skills/synaptiai/synapti-marketplace/nci-analysis.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 | $0.00075 | $0.03273 |
| Opus 5 | $0.00037 | $0.01636 |
| Sonnet 5 | $0.00015 | $0.00655 |
| Haiku 4.5 | $0.00007 | $0.00327 |
Grade A, and why
nci-manipulation-analysis 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 7d 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 — 414 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NCI Manipulation Analysis
This skill uses pattern-based manipulation detection that identifies how content tries to influence the reader, not whether claims are factually true. Manipulation techniques leave fingerprints regardless of underlying accuracy.
Use TodoWrite to track these mandatory steps:
Quick Start
For Text Content
- Read the content provided by user
- Apply 20-category analysis (see references/categories.md)
- Calculate composite factors and overall score (see references/scoring.md)
- Check deep research triggers - if score > 40 or key categories elevated, verify claims
- Generate dual perspectives
- Output report in requested format
For URLs
- Use
WebFetchto retrieve content from URL - Extract main article/post text
- Proceed with text analysis workflow
- Note source metadata (publication, date, author)
- If triggers met: Use
fact-checkeragent to verify key claims
First Principles (Summary)
The NCI Protocol is grounded in these principles (see agents/perspective-generator.md for full version):
- Evidence over authority - Evaluate patterns in content, not source reputation
- Steel-man interpretation - Present strongest version of each perspective
- Atomic decomposition - Break claims into smallest verifiable units
- Source agnosticism - Apply identical standards regardless of source alignment
- Bidirectional beneficiary analysis - Ask who benefits if believed AND if dismissed
- Pattern vs. Intent - Focus on techniques; deep research evidence can inform motives
These principles ensure fair, consistent analysis across all content regardless of political or ideological alignment.
What ships with it
5 files 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.
- 7d ago First seen · 414 lines · 75 tokens per session scan A 360f5e9cdb76
nci-manipulation-analysis is a skill published in the GitHub repository synaptiai/synapti-marketplace (6 stars, last pushed today), licensed Apache-2.0. It adds 75 tokens to every session and 3,273 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 2026-09-03.
Other skills, from other repositories
create-or-update-concepts
Scan and analyze the project codebase to create or update concept files in agents-context/concepts/ (organized by domains/, source/, shared/) and update the README index and Load-When Cheatsheet.
step2-scope-tasks
Break a specification into ordered task groups with explicit context-awareness directives.
step1-write-spec
Gather requirements through structured Q&A, then formalize into a specification document.
create-pr
Creates a GitHub Pull Request on the current branch with a description focused on WHAT changed (not HOW). Uses emojis in the title and description. Use when the user asks to create a PR, open a pull request, or submit changes for review. Triggers on mentions of PR, pull request, merge request, or code review.
plan-product
Define product mission, vision, target users, and technology stack.
step4-archive-spec
Archive a completed spec — moves it to specs-archived and blocks agent access.