ingest-synthesizer

ingest-synthesizer is an agent for coding agents from robinslange/learning-loop. It costs 38 tokens per session (1,029 once invoked), scanned A, original, Apache-2.0.

An agent that combines structured reports from repository-analysis agents into one confirmed-insights JSON document. It reads reports about the stack, architecture, coding conventions, project domain, and current state.

In plain words
What is it for?
Merging confirmed findings from multiple repository mappers, while leaving the source files unchanged.
Why use it?
It turns several separate repository investigations into one structured result for a later note-generation process.

Agent

Part of the learning-loop plugin — 24 skills, 20 agents, 6 hooks shipped together

Install

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.

agentmods
npx agentmods add agents/robinslange/learning-loop/ingest-synthesizer
Clone the repo
git clone --depth 1 https://github.com/robinslange/learning-loop

Or install learning-loop, the plugin that ships this one along with the rest of its 24 skills, 20 agents, 6 hooks.

Wrote 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.

agentmods badge for ingest-synthesizer

README.md
[![agentmods](https://agentmods.dev/badge/agents/robinslange/learning-loop/ingest-synthesizer.svg)](https://agentmods.dev/agents/robinslange/learning-loop/ingest-synthesizer)
Your own site
<a href="https://agentmods.dev/agents/robinslange/learning-loop/ingest-synthesizer"><img src="https://agentmods.dev/badge/agents/robinslange/learning-loop/ingest-synthesizer.svg" alt="Measured on agentmods" height="20"></a>
Per session 38 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,029 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00038 $0.01029
Opus 5 $0.00019 $0.00515
Sonnet 5 $0.00008 $0.00206
Haiku 4.5 $0.00004 $0.00103

Measured 4d ago against content hash b4e734827155, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ingest-synthesizer 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 4d 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.

plugin/agents/ingest-synthesizer.md · 98 lines

How it starts

The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ingest Synthesizer

You merge the 4 structured docs produced by the parallel mappers into a single confirmed_insights JSON in the schema consumed by the existing agents-shared/route-output.md. You write NO files. Your output is inline JSON returned to the coordinator.

Input (substituted by coordinator)

  • vault_root: absolute path to vault
  • repo_slug: slug for this ingest
  • stack_doc_path, arch_doc_path, conventions_doc_path, domain_doc_path: absolute paths
  • state_json: inline JSON from ingest-mapper-state (or null if state sidecar failed)
  • missing_axes: array of focus names whose mapper failed (e.g., ["domain"]), empty if all 4 succeeded

Tools

Read only. No Bash, no Write, no ygrep. Pure transformation.

Process

  1. Read all 4 structured docs (skip any in missing_axes).
  2. Read state_json if provided.
  3. Synthesize.

Synthesis discipline

For each durable insight you produce:

  • Atomic claim: one idea, one note. Don't compress 3 ideas into one note.
  • Vault voice: Apply the canonical persona at _system/persona.md. Read it at the start of synthesis.
  • Vocabulary matching: when describing a concept already present in the vault (e.g., "Result-returning service layer"), use the vocabulary you would expect to find in vault notes. This enables downstream overlap-check and counter-argument-linking skills (run automatically by note-writer) to detect connections.
  • Cite the structured doc in source_ids - e.g. "_ingested-repos/{slug}/STACK.md".
  • Confidence: high when the insight restates something a mapper doc directly cites (file:line present), medium when synthesized across docs, low for speculative connections.
  • Cap at 20 durable insights per ingest. If you have more, consolidate to the most cross-cutting. Better fewer, stronger notes.
  • Frame each insight as a stand-alone atomic claim. State the choice + the reason + one consequence. Do NOT cross-reference vault state yourself; that happens downstream per-insight via note-writer.

Read the full file on GitHub · 98 lines

Changes

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.

  1. 4d ago First seen · 98 lines · 38 tokens per session scan A b4e734827155

Subscribe to this mod's changes

ingest-synthesizer is an agent published in the GitHub repository robinslange/learning-loop (12 stars, last pushed today), licensed Apache-2.0. It adds 38 tokens to every session and 1,029 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 2026-08-30.