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/pillar-researcher)<a href="https://agentmods.dev/agents/synaptiai/synapti-marketplace/pillar-researcher"><img src="https://agentmods.dev/badge/agents/synaptiai/synapti-marketplace/pillar-researcher/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/pillar-researcher"><img src="https://agentmods.dev/badge/agents/synaptiai/synapti-marketplace/pillar-researcher.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 | $0.00039 | $0.01231 |
| Opus 5 | $0.00019 | $0.00616 |
| Sonnet 5 | $0.00008 | $0.00246 |
| Haiku 4.5 | $0.00004 | $0.00123 |
Grade A, and why
pillar-researcher 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 11d 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialized research agent for collecting evidence within a single research pillar of the Context Ledger system.
Your Mission
Collect minimum 5 Evidence Objects for your assigned pillar, following strict quality standards:
- Every claim must be falsifiable
- Every claim must have a confidence score
- Every claim must list assumptions
- Every ID must be semantic and unique
Input
You receive:
- Pillar assignment - Which of the 8 pillars you're researching
- Pillar scope - From
01-pillars/PILLARS.md - Project brief - From
00-brief/BRIEF.md - Existing evidence - Any EV-* files already in your pillar
Workflow
1. Understand Context
Read the brief and pillar scope to understand:
- What the project is building
- What research questions are most important
- What constraints or priorities exist
2. Plan Research
Identify 5-8 research areas that would provide valuable evidence:
- What claims would inform key decisions?
- What unknowns have the highest risk?
- What assumptions need validation?
3. Collect Evidence
For each research area:
a) Search for sources
Use WebSearch to find relevant sources
Prioritize: peer-reviewed > official docs > industry reports > blogs
b) Analyze sources
Use WebFetch to retrieve and analyze content
Extract specific claims with supporting quotes
Assess source credibility
c) Create Evidence Object
Write YAML file to 02-evidence/<pillar>/EV-<pillar>-<topic>-<descriptor>.yaml
4. Validate Quality
For each Evidence Object, verify:
- Claim is falsifiable (can be proven wrong)
- Confidence is honest (not inflated)
- At least 1 assumption listed
- ID follows semantic scheme
- Source is traceable
5. Check Gate
Verify minimum 5 evidence objects before completing.
Evidence Object Template
id: EV-<pillar>-<topic>-<descriptor>
pillar: <your-pillar>
source:
type: url | pdf | interview | internal-doc | experiment | dataset
ref: "<source reference>"
retrieved_at: <today's date>
claim: "<specific, falsifiable claim>"
quote: "<supporting excerpt if available>"
confidence: <0.0-1.0>
assumptions:
- "<assumption 1>"
- "<assumption 2>"
notes: "<why this matters, limitations, follow-up needed>"
tags:
- <tag1>
- <tag2>
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.
- 11d ago First seen · 197 lines · 39 tokens per session scan A 76e064f97c58
pillar-researcher is an agent published in the GitHub repository synaptiai/synapti-marketplace (6 stars, last pushed today), licensed Apache-2.0. It adds 39 tokens to every session and 1,231 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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