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/commands/synaptiai/synapti-marketplace/report)<a href="https://agentmods.dev/commands/synaptiai/synapti-marketplace/report"><img src="https://agentmods.dev/badge/commands/synaptiai/synapti-marketplace/report/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/commands/synaptiai/synapti-marketplace/report"><img src="https://agentmods.dev/badge/commands/synaptiai/synapti-marketplace/report.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 | $0.00016 | $0.01628 |
| Opus 5 | $0.00008 | $0.00814 |
| Sonnet 5 | $0.00003 | $0.00326 |
| Haiku 4.5 | $0.00002 | $0.00163 |
Grade A, and why
report 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 9d 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 — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate NCI Report
Generate formal NCI analysis report in JSON or Markdown format.
Usage
/decipon:report <URL or text> [--format json|markdown] [--output filename]
Arguments
$ARGUMENTS: Content to analyze plus optional flags- Content: URL, file path, or text
--format: Output format (default: markdown)--output: Save to file (optional)
Purpose
Generate a formal, shareable NCI analysis report:
- Complete 20-category breakdown
- Dual perspectives with confidence
- Structured format for sharing/archiving
- Machine-readable (JSON) or human-readable (Markdown)
Workflow
-
Parse Arguments
- Extract content from flags
- Determine output format
- Identify output file if specified
-
Perform Full Analysis
- Invoke NCI skill
- Score all 20 categories with evidence
- Calculate all metrics
-
Generate Perspectives
- Manipulative interpretation
- Legitimate interpretation
- Confidence levels for both
-
Format Report
- Apply requested format (JSON or Markdown)
- Include all metadata
-
Output/Save
- Display to user
- Save to file if
--outputspecified
Markdown Report Format
# NCI Analysis Report
**Generated**: [ISO timestamp]
**Protocol Version**: 1.0
**Content Source**: [URL or "Direct input"]
---
## Executive Summary
**Overall Score**: 72/100 [!!!]
**Confidence**: 82%
**Risk Level**: HIGH
**Key Finding**: This content exhibits strong manipulation patterns,
particularly in emotional manipulation and missing information dimensions.
---
## Composite Factor Scores
### Emotional Manipulation: 4.2/5
Confidence: 85%
| Category | Score | Evidence |
|----------|-------|----------|
| Base Emotional | 4 | [Evidence] |
| Urgent Action | 5 | [Evidence] |
| Novelty | 4 | [Evidence] |
| Repetition | 4 | [Evidence] |
| Manufactured Outrage | 4 | [Evidence] |
### Suspicious Timing: 4.7/5
[Continue for each composite...]
---
## Perspectives
### Manipulative Interpretation
**Confidence**: 80%
[Full manipulative interpretation...]
### Legitimate Interpretation
**Confidence**: 55%
[Full legitimate interpretation...]
---
## Detailed Category Analysis
[All 20 categories with full evidence...]
---
## Methodology
This analysis follows NCI Protocol v1.0:
- Pattern-based detection (not truth-based)
- 20 manipulation indicators across 5 dimensions
- Weighted scoring with confidence metrics
- Dual perspective generation
---
## Appendix: Raw Scores
[JSON-formatted raw data for programmatic use]
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.
- 9d ago First seen · 290 lines · 16 tokens per session scan A 884d5656813a
report is a command published in the GitHub repository synaptiai/synapti-marketplace (6 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 16 tokens to every session and 1,628 once invoked, about $0.0001 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 commands, from other repositories
create-worktree
Follow these steps to create a git worktree.
paper-trail-review
Review and arbitrate problematic references (cascade-exhausted, unresolved UID, awaiting OCR). Generates an up-to-date report, walks through cases by category, and applies arbitration decisions to the registry.
paper-trail-new-paper
Start writing an academic paper (IMRaD structure) on a topic, with anti-hallucination citation verification at every step. Builds on existing audited SOTAs.
paper-trail-registry-cleanup
Nettoyage historique du registre des fiches bibliographiques (les 900 fiches existantes). Cible les vieilles fiches mal nommées (0000, untitled) ET les duplicates avec suffixes numériques (foo2020bar2, 234) qui sont des artefacts de runs INGEST passés. Délègue les décisions au sub-agent textbook-resolver. Les merge…
paper-trail-cascade
Acquire PDFs via the 8-source cascade (11 with opt-in extended sources) for a single ref by slug, or a batch filtered by state. Validates page 1 anti-homonymy on each download.
paper-trail-linkify
Dernière passe du pipeline cible refondu. Insère les wikilinks finaux dans le SOTA (vers PDF si validé, sinon vers ancre dans une section ## Statut des sources régénérée idempotemment en bas du fichier). Présuppose que les passes identify/purge/acquire ont été lancées.