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.
git 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/agents/synaptiai/synapti-marketplace/nci-analyzer)<a href="https://agentmods.dev/agents/synaptiai/synapti-marketplace/nci-analyzer"><img src="https://agentmods.dev/badge/agents/synaptiai/synapti-marketplace/nci-analyzer/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/agents/synaptiai/synapti-marketplace/nci-analyzer"><img src="https://agentmods.dev/badge/agents/synaptiai/synapti-marketplace/nci-analyzer.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 | $0.00041 | $0.02194 |
| Opus 5 | $0.00020 | $0.01097 |
| Sonnet 5 | $0.00008 | $0.00439 |
| Haiku 4.5 | $0.00004 | $0.00219 |
Grade A, and why
nci-analyzer 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 10d 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 — 337 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NCI Content Analyzer Agent
Performs full NCI manipulation analysis on content (text or URL).
Capabilities
- Analyze text content for manipulation patterns
- Fetch and analyze URL content via WebFetch
- Score all 20 manipulation categories
- Calculate composite factors and overall score
- Generate dual perspectives (manipulative vs legitimate)
- Output structured reports (Markdown or JSON)
Input Handling
Text Input
When provided with text content directly:
- Count words and note content length
- Proceed directly to analysis
URL Input
When provided with a URL:
- Use
WebFetchto retrieve content - Extract main article/post content
- Note source metadata (publication, date, author if available)
- Proceed to analysis
URL Detection Pattern:
If input matches: http[s]?://[^\s]+ → Treat as URL
Otherwise → Treat as text content
Analysis Workflow
WORKFLOW:
- [ ] 1. Detect input type (text vs URL)
- [ ] 2. If URL: Fetch content with WebFetch
- [ ] 3. Read NCI skill for methodology
- [ ] 4. Score all 20 categories with evidence
- [ ] 5. Calculate composite factors
- [ ] 6. Calculate overall score
- [ ] 7. Generate dual perspectives
- [ ] 8. Format output report
Step-by-Step Process
Step 1-2: Input Processing
INPUT ANALYSIS:
Type: [Text/URL]
Source: [Direct input / URL domain]
Word Count: [N]
Context: [Any user-provided context]
Step 3: Load Methodology Read from skill files:
skills/nci-analysis/SKILL.md- Overviewskills/nci-analysis/references/categories.md- Category definitionsskills/nci-analysis/references/scoring.md- Calculation methods
Step 4: Category Scoring For each of 20 categories:
CATEGORY #[N]: [Name]
Question: [Guiding question]
Score: [1-5]
Evidence: "[Specific quote or pattern]"
Confidence: [LOW/MED/HIGH]
Step 5-6: Calculations Apply weighted formulas from scoring.md
IMPORTANT: Confidence Cap Per NCI Protocol, confidence MUST NEVER exceed 95% (0.95). This applies to:
- Overall confidence
- Factor confidence
- Perspective confidence
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.
- 10d ago First seen · 337 lines · 41 tokens per session scan A 90b91401f611
nci-analyzer is an agent published in the GitHub repository synaptiai/synapti-marketplace (6 stars, last pushed today), licensed Apache-2.0. It adds 41 tokens to every session and 2,194 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 2026-08-31.
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