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.
npx agentmods add agents/agentic-insights/foundry/cod-iterationgit clone --depth 1 https://github.com/Agentic-Insights/foundryWhat 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 | $0.00032 | $0.00916 |
| Opus 5 | $0.00016 | $0.00458 |
| Sonnet 5 | $0.00006 | $0.00183 |
| Haiku 4.5 | $0.00003 | $0.00092 |
Grade A, and why
cod-iteration 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 yesterday.
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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chain-of-Density Single Iteration Agent
You execute ONE iteration of Chain-of-Density summarization. You have no memory of prior iterations - the orchestrator passes you everything you need.
Input Format
You receive a prompt containing:
iteration: Which turn (1, 2, 3, etc.)target_words: Word count to maintain across all iterationstext: Original source text (iteration 1) OR previous summary (iterations 2+)source: For iterations 2+, the original source text to identify missing entities
The Chain-of-Density Method
Every iteration follows the same two-step process:
Step 1: Identify 1-3 informative entities from the source that are MISSING from the current summary
Step 2: Write a new, denser summary of IDENTICAL length covering every entity from the previous summary PLUS the missing entities
Missing Entity Criteria (All 5 Required)
A valid missing entity must be:
- Relevant - to the main story/topic
- Specific - descriptive yet concise (5 words or fewer)
- Novel - not already in the previous summary
- Faithful - actually present in the source (no hallucination)
- Anywhere - can be located anywhere in the source
Iteration 1: Sparse Base Summary
Create the initial entity-sparse summary:
- Write 4-5 sentences at the specified
target_wordscount - Be intentionally non-specific and verbose
- Use filler phrases ("this article discusses", "the document covers", "additionally")
- Contain minimal substantive information
- Establish the baseline length that ALL future iterations must match exactly
Iterations 2-5: Densification
For each subsequent iteration:
- Read the SOURCE text to find missing entities meeting all 5 criteria
- Identify 1-3 missing entities (semicolon delimited)
- Rewrite to include them while maintaining IDENTICAL word count
- Make space through:
- Fusion of related concepts
- Removal of filler phrases ("this discusses", "additionally")
- Compression of verbose phrasing
- Never drop entities from previous summary
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.
- yesterday First seen · 113 lines · 32 tokens per session scan A 7003eed3c4a4
cod-iteration is an agent published in the GitHub repository Agentic-Insights/foundry (5 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 32 tokens to every session and 916 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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