Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligencenpx agentmods add skills/agentii-ai/agentii-investment-intelligence/convergeWrote 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/skills/agentii-ai/agentii-investment-intelligence/converge)<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/converge"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/converge/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/skills/agentii-ai/agentii-investment-intelligence/converge"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/converge.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 | $0.00093 | $0.00652 |
| Opus 5 | $0.00046 | $0.00326 |
| Sonnet 5 | $0.00019 | $0.00130 |
| Haiku 4.5 | $0.00009 | $0.00065 |
Grade A, and why
converge 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 today.
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
agentii.converge
Append-only gap closure — the cadence engine of the research orchestration system (spec 046 Q26).
When to run
- After every
agentii.implementbatch (the system detects its own staleness). - On any cadence cycle (quarterly re-visits, post-earnings, post-constitution-bump).
- Before any IC review (the conflict list must be current).
- When the cross-stock synthesis tasks complete, close the loop with the report
workflow — see
skills/agentii/synthesize/SKILL.md(pack → author content.html → assemble). Anhtml_stalefinding below means that workflow must re-run.
What it does
- Evaluates current state — artifacts on disk, pins in frontmatter,
wrong_iffalsifiers inthesis.md. It never reads git history and never trusts[x]checkboxes (Q26 A+: the ledger may lie; the correction is deterministic and has a bounded expiry — the next converge). - Appends, never rewrites — the only write is a
## Phase N: Convergencesection at the end oftasks.md, withsrc:refs and content-derived finding IDs. Existing lines, including previous Convergence sections, are untouched. - Clean run = byte-identical — no gaps means no empty section header.
Gap types
| Type | Class | Cap |
|---|---|---|
stale (pins older than current) |
deterministic | uncapped |
invalidated (wrong_if metric+threshold triggered) |
deterministic | uncapped |
missing / partial / contradicts / unrequested |
judgment | Q40 cap (≈50) |
Invocation
python3 scripts/converge.py --thesis theses/001-ai-semiconductors \
--pins '{"assumption_pin": 1, "corpus_version": "2026-08", "as_of": "2026-09-08", "constitution_pin": "0.1.0", "skill_pin": "recent-quarter:abc"}'
Hard rules (Q26)
- Never modify
spec.mdorplan.md. - Never rewrite, renumber, reorder, or delete any existing task.
- Finding IDs are content-derived (
hash(entity+metric+period+gap_type)) — an unchanged re-run appends nothing.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- today Changed · +4 lines 12e69012c09b
- yesterday First seen · 52 lines · 93 tokens per session scan A efbcad4f4984
converge is a skill published in the GitHub repository agentii-ai/agentii-investment-intelligence (204 stars, last pushed today), licensed Apache-2.0. It adds 93 tokens to every session and 652 once invoked, about $0.0005 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 2026-09-09.
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