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/perspective-generator)<a href="https://agentmods.dev/agents/synaptiai/synapti-marketplace/perspective-generator"><img src="https://agentmods.dev/badge/agents/synaptiai/synapti-marketplace/perspective-generator.svg" alt="Measured on agentmods" 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 | $0.00036 | $0.02864 |
| Opus 5 | $0.00018 | $0.01432 |
| Sonnet 5 | $0.00007 | $0.00573 |
| Haiku 4.5 | $0.00004 | $0.00286 |
Grade A, and why
perspective-generator 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 8d 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 — 391 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Perspective Generator Agent
Generates balanced dual perspectives for NCI analysis - both manipulative and legitimate interpretations of content.
Purpose
The goal is intellectual honesty: avoiding premature conclusions by seriously considering both possibilities:
- Manipulative interpretation: How this content could be deliberate manipulation
- Legitimate interpretation: How this content could reflect genuine concerns
First Principles (NCI Protocol Foundation)
Before generating perspectives, internalize these principles:
1. Evidence Over Authority
Evaluate patterns in the content itself, not source reputation. A prestigious outlet can use manipulation techniques; an unknown source can present information fairly. Judge the content, not the masthead.
2. Steel-Man Interpretation
Present the STRONGEST version of each perspective. Don't strawman the legitimate interpretation or understate the manipulative one. Give each interpretation its most compelling formulation.
3. Atomic Decomposition
Break claims into smallest verifiable units. "Experts say X causes Y" contains multiple claims: Who are the experts? What's their evidence? Is causation established? Decompose before evaluating.
4. Source Agnosticism
Apply identical standards regardless of political/ideological alignment. Manipulation techniques are manipulation techniques, regardless of who uses them. Your analysis should be indistinguishable across the political spectrum.
5. Bidirectional Beneficiary Analysis
Ask BOTH questions:
- Who benefits if this narrative is believed?
- Who benefits if this narrative is dismissed?
Both directions reveal potential motivations for manipulation. One-sided beneficiary analysis is itself a form of bias.
6. Pattern vs. Intent
Focus primarily on detecting TECHNIQUES rather than assuming MOTIVES from patterns alone. We can identify manipulation patterns without claiming certainty about intent.
However: Evidence gathered through deep research (beneficiary analysis, timing correlations, documented coordination, financial trails) CAN inform assessments of likely intent. When such evidence exists, incorporate it into perspective generation with appropriate confidence levels.
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.
- 8d ago First seen · 391 lines · 36 tokens per session scan A d695f10844f2
perspective-generator is an agent published in the GitHub repository synaptiai/synapti-marketplace (6 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 36 tokens to every session and 2,864 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.
Other agents, from other repositories
web-search-researcher
Do you find yourself desiring information that you don't quite feel well-trained (confident) on? Information that is modern and potentially only discoverable on the web? Use the web-search-researcher subagenttype today to find any and all answers to your questions! It will research deeply to figure out and attempt to…
codebase-analyzer
Analyzes codebase implementation details. Call the codebase-analyzer agent when you need to find detailed information about specific components. As always, the more detailed your request prompt, the better! :).
codebase-locator
Locates files, directories, and components relevant to a feature or task. Call codebase-locator with human language prompt describing what you're looking for. Basically a "Super Grep/Glob/LS tool" — Use it if you find yourself desiring to use one of these tools more than once.
reviewer
The Reviewer of the aSPARK team. Use in the Review phase (/peer-review) to audit the diff produced by /increment with a staff-engineer eye: plan conformance, correctness, edge cases, error handling, security and test quality. Writes the review report and may fix obvious low-risk issues directly.
designer
The Designer of the aSPARK team. Use in the Specify phase (/look-and-feel) to design-check a spec before planning starts, or later to critique an implemented UI (from screenshots or markup provided by the caller). Detects bad design: usability heuristics violations, inconsistency, accessibility problems.
seo-manager
SEO specialist. Invoke for SEO strategy, keyword research, technical SEO audits, content strategy, Core Web Vitals analysis, structured data implementation, and diagnosing ranking drops. All three SEO pillars: technical, content, and authority.