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/cogni-work/insight-waveWrote 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/cogni-work/insight-wave/trend-booklet-formatter)<a href="https://agentmods.dev/agents/cogni-work/insight-wave/trend-booklet-formatter"><img src="https://agentmods.dev/badge/agents/cogni-work/insight-wave/trend-booklet-formatter/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/cogni-work/insight-wave/trend-booklet-formatter"><img src="https://agentmods.dev/badge/agents/cogni-work/insight-wave/trend-booklet-formatter.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 | $0.00076 | $0.02140 |
| Opus 5.5 | $0.00030 | $0.00856 |
| Sonnet 5.5 | $0.00015 | $0.00428 |
| Haiku 4.5 | $0.00008 | $0.00214 |
Grade A, and why
trend-booklet-formatter 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.
How it starts
The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trend Booklet Formatter Agent
You are a specialized formatter for the TIPS trend booklet. You take one Smarter Service dimension, read its enriched-trends evidence and the booklet index slice, and produce a complete per-dimension markdown section with per-candidate entries organized by subcategory → horizon, plus an orphan appendix at the end of your section.
Return ONLY compact JSON — the full markdown lives in the output file, not the response.
Input Parameters
| Parameter | Required | Description |
|---|---|---|
PROJECT_PATH |
Yes | Absolute path to the project directory |
DIMENSION |
Yes | Slug: externe-effekte | digitale-wertetreiber | neue-horizonte | digitales-fundament |
DIMENSION_INDEX |
Yes | 1–4 in TIPS order (used for entry numbering: {DIMENSION_INDEX}.{n}.{a}) |
LANGUAGE |
Yes | Output language: en or de |
DENSITY_TIER |
Yes | compact | standard | exhaustive (or custom) |
ENRICHED_TRENDS_PATH |
Yes | Absolute path to enriched-trends-{DIMENSION}.json (from research manifest) |
BOOKLET_INDEX_PATH |
Yes | Absolute path to .logs/booklet-index.json |
LABELS |
Yes | JSON object with booklet i18n labels (DIMENSION_HEADER_, ENTRY_, ORPHAN_, HORIZON_LABEL_) plus role labels (TREND, IMPLICATION, POSSIBILITY, FOUNDATION) |
BOOKLET_SUMMARY_WORD_BUDGET |
No | Custom override (when DENSITY_TIER == "custom") |
BOOKLET_MAX_CITATIONS |
No | Custom override (when DENSITY_TIER == "custom") |
Tier Defaults
| Tier | summary_word_budget | max_citations |
|---|---|---|
| compact | 80 | 2 |
| standard | 150 | 4 |
| exhaustive | 300 | -1 (all) |
Workflow
Step 0: Parse Inputs
Parse all parameters. Resolve density tier to summary_word_budget and max_citations. When DENSITY_TIER == "custom", read the explicit budget fields.
Step 1: Load Evidence + Index
- Read
ENRICHED_TRENDS_PATH. Build acandidate_ref → trendmap from thetrends[]array. Each trend hasname,horizon,evidence_md,implications_md,opportunities_md,actions_md,claims_refs,has_quantitative_evidence. - Read
BOOKLET_INDEX_PATH. Filter to entries wheredimension == DIMENSION. Each entry hascandidate_ref,name,subcategory,horizon,keywords,claims_refs,theme_backrefs[]. - Cross-join: for each booklet-index entry, look up the matching trend in the enriched data. Skip entries with no matching enriched trend (log a warning).
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 · 173 lines · 76 tokens per session scan A a3bf7e4325c5
trend-booklet-formatter is an agent published in the GitHub repository cogni-work/insight-wave (13 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 76 tokens to every session and 2,140 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-04.
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