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/plugins/synaptiai/synapti-marketplace/context-ledger)<a href="https://agentmods.dev/plugins/synaptiai/synapti-marketplace/context-ledger"><img src="https://agentmods.dev/badge/plugins/synaptiai/synapti-marketplace/context-ledger/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/plugins/synaptiai/synapti-marketplace/context-ledger"><img src="https://agentmods.dev/badge/plugins/synaptiai/synapti-marketplace/context-ledger.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
context-ledger 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 1mo 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.
What it actually says
{
"name": "context-ledger",
"version": "1.0.0",
"description": "Structured product development methodology with traceable evidence, explicit decisions, and constrained spec generation. Forces auditability through semantic IDs, quality gates, and impact-aware updates.",
"author": {
"name": "Synapti AI",
"url": "https://github.com/synaptiai"
},
"repository": "https://github.com/synaptiai/synapti-marketplace",
"homepage": "https://github.com/synaptiai/synapti-marketplace/tree/main/plugins/context-ledger",
"license": "Apache-2.0",
"keywords": [
"product-development",
"evidence-based",
"decision-ledger",
"traceability",
"prd",
"architecture",
"risk-management",
"constrained-generation",
"semantic-ids",
"quality-gates"
]
}
What it installs
The manifest is a name and a version. 5 skills, 8 commands, 5 agents travel with it, and installing the plugin installs all of them — 438 tokens a session between them. Each is measured on its own page, and each can be installed alone.
- Skill collecting-evidence A 36 tokens
- Skill generating-constrained-specs A 37 tokens
- Skill initializing-ledger A 30 tokens
- Skill making-decisions A 25 tokens
- Skill synthesizing-pillars A 36 tokens
- Command ledger-decide A 12 tokens
- Command ledger-plan A 16 tokens
- Command ledger-research A 9 tokens
- Command ledger-synthesize A 14 tokens
- Command ledger-update A 17 tokens
- Command ledger-init A 15 tokens
- Command ledger-spec A 12 tokens
- Command ledger-full B 0 tokens
- Agent cross-synthesizer A 42 tokens
- Agent ledger-orchestrator A 32 tokens
- Agent pillar-researcher A 39 tokens
- Agent pillar-synthesizer A 34 tokens
- Agent spec-architect A 32 tokens
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.
- 1mo ago First seen · 25 lines scan A d0e8150c40f3
context-ledger is a plugin published in the GitHub repository synaptiai/synapti-marketplace (7 stars, last pushed 4d ago), licensed Apache-2.0. Its token cost is not measured: this kind of file is read by the harness, not the model. 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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