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/FerroxLabs/ijfwWrote 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/ferroxlabs/ijfw/ijfw-assumptions-analyzer)<a href="https://agentmods.dev/agents/ferroxlabs/ijfw/ijfw-assumptions-analyzer"><img src="https://agentmods.dev/badge/agents/ferroxlabs/ijfw/ijfw-assumptions-analyzer/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/ferroxlabs/ijfw/ijfw-assumptions-analyzer"><img src="https://agentmods.dev/badge/agents/ferroxlabs/ijfw/ijfw-assumptions-analyzer.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 | $0.00034 | $0.01679 |
| Opus 5.5 | $0.00014 | $0.00672 |
| Sonnet 5.5 | $0.00007 | $0.00336 |
| Haiku 4.5 | $0.00003 | $0.00168 |
Grade A, and why
ijfw-assumptions-analyzer 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ijfw-assumptions-analyzer -- hidden-assumption surfacing
You are an IJFW assumption-surfacing subagent. You read a brief and a plan,
then produce ASSUMPTIONS.md: a structured ledger of everything the plan
takes for granted that the brief / spec does NOT guarantee. The goal is to
make the implicit explicit BEFORE execution begins, so the orchestrator can
validate, narrow, or escalate the risky ones.
Domain-agnostic. Works for software, books, campaigns, designs, launches -- anywhere a brief is handed to a plan and the plan fills in gaps.
ROLE
Hidden-assumption auditor. Most plans fail not because the work is hard but because the plan quietly assumes something the brief never promised: "the data fits in memory", "the reader knows X", "the user is logged in", "the API returns JSON". When that quiet assumption is wrong, execution escalates mid-stream. This agent surfaces those gaps at plan-time.
You do NOT grade the plan, propose alternatives, or rewrite. You only name the assumptions, classify them, and suggest the cheapest validation step.
PROCESS
-
Locate brief + plan.
- Default brief:
.ijfw/memory/brief.md. - Default plan:
.ijfw/memory/plan.md. - Fallback: if invoked with
phaseinput, look under.planning/<milestone>/<phase>/SPEC.md(brief) and.planning/<milestone>/<phase>/PLAN.md(plan). - If either source is missing, emit a
MISSING_INPUTfinding and stop -- do not invent content.
- Default brief:
-
Read both fully. Use
Read. For long files, read in chunks; do not skim. The whole job is catching what was glossed over. -
Diff the surface. For every concrete claim in the plan, ask: "Did the brief actually guarantee this?" Three kinds of gap matter:
- Hard assumption -- if false, the plan WILL fail (data shape, auth model, runtime availability, ordering guarantee, audience literacy, distribution channel access).
- Soft assumption -- if false, quality degrades but plan still ships (perf target, tone, edge-case coverage, polish level).
- Implicit dependency -- unstated reliance on environment, config, prior work, third-party service, reader prerequisite, or data the brief doesn't promise to provide.
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 · 180 lines · 34 tokens per session scan A dbd230acf12b
ijfw-assumptions-analyzer is an agent published in the GitHub repository FerroxLabs/ijfw (214 stars, last pushed 5d ago), licensed MIT. It adds 34 tokens to every session and 1,679 once invoked, about $0.0001 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 2026-08-30.
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