Borrowing it
Nothing to install: this file belongs to zkysar1/Claude-Mind. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zkysar1/Claude-Mind/main/.claude/skills/review-hypotheses/SKILL.mdgit clone --depth 1 https://github.com/zkysar1/Claude-MindWrote 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/zkysar1/claude-mind/review-hypotheses)<a href="https://agentmods.dev/skills/zkysar1/claude-mind/review-hypotheses"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/review-hypotheses/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/zkysar1/claude-mind/review-hypotheses"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/review-hypotheses.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00094 | $0.13120 |
| Opus 5 | $0.00047 | $0.06560 |
| Sonnet 5 | $0.00019 | $0.02624 |
| Haiku 4.5 | $0.00009 | $0.01312 |
Grade A, and why
review-hypotheses 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.
How it starts
The opening of the file, as written. The whole thing — 1,077 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/review-hypotheses — Hypothesis Review & Resolution Engine
Two-phase design: resolve (detect outcomes, move records, record results) and learn (reflect on outcomes, extract patterns). These phases are separated so that /boot can resolve without triggering learning, and /aspirations goals can learn from freshly resolved data without re-checking resolution sources.
Parameters
--resolve— Check resolution status, move active→resolved, record outcomes. Does NOT call /reflect. Setsreflected: falseon each record.--learn— Find resolved records withreflected: false, call/reflect --on-hypothesisfor each, setreflected: true.--accuracy-report— Generate accuracy statistics across all resolved hypotheses--full-cycle—--resolve+--learn+--accuracy-report+/reflect --full-cycle+ spark check--category-comparison <cat1> <cat2>— Compare accuracy between two categories--hypothesis <id>— Check a specific hypothesis- When called as a goal's skill (from aspirations loop), returns one of:
CONFIRMED— hypothesis confirmed (move pipeline file to resolved/)CORRECTED— hypothesis disconfirmed (move pipeline file to resolved/)PENDING— not enough evidence yet (goal stays pending for retry)EXPIRED— past resolves_by deadline (move pipeline file to archived/)
- When called as a goal's skill (from aspirations loop), returns one of:
- No args → default to
--resolve
Step 0: Load Conventions
Step 0: Load Conventions — Bash: load-conventions.sh with each name from the conventions: front matter. Read only the paths returned (files not yet in context). If output is empty, all conventions already loaded — proceed to next step.
Mode 1: Resolve (--resolve)
Detects which active hypotheses have resolved, records outcomes, moves records, and updates the memory tree. Does NOT trigger reflection or learning — that is --learn's job.
Step 1: Load Hypotheses to Check
# Step 1.0: Pre-scan discovered-stage records orphaned past resolves_by (g-115-1629).
# review-hypotheses historically loaded ONLY active + measurement-pending, so
# discovered records past resolves_by were invisible -- never resolved, never
# fed accuracy stats (63 of 193 orphaned at filing, oldest >2mo). This sweep
# EXPIRES clearly-unresolvable ones (short/session horizon past the observation
# window -> archived UNRESOLVABLE, gate-exempt) and PROMOTES well-formed
# evaluable ones to active so the resolution loop below catches them THIS run.
# Direct py -3 (not a bash wrapper) per rb-225/rb-247.
Bash: py -3 core/scripts/hypothesis-discovered-overdue-sweep.py --apply --output json
# Parse {expired, promoted, needs_judgment}. `promoted` records are now
# stage=active and WILL appear in the active load below (resolved this run).
# `needs_judgment` (under-formed, recently overdue) are SURFACED, not auto-
# resolved: for each, if evaluable, synthesize a claim from the position
# (guard-798: leaving discovered needs claim>=20 + a resolution method), then
# resolve/expire with judgment; else leave for the next cycle.
#
# ELIGIBLE LANE (g-115-4721). The sweep ALSO returns {eligible,
# eligible_promoted, eligible_needs_judgment}: discovered records past their
# eligibility floor but NOT yet overdue -- the interval that was watched by
# nothing, and the one where a hypothesis is MOST resolvable (in-window, channel
# live, evidence still cheap). eligible_promoted is already folded into
# `promoted`, so it needs no separate handling. Handle `eligible_needs_judgment`
# exactly like needs_judgment WITH ONE EXCEPTION: never EXPIRE one -- its
# observation window is still open, and expiring it is the harm the lane exists
# to prevent. A future resolves_no_earlier_than is respected as a deliberate
# park, so nothing still parked appears in either bucket.
# READ `eligible`, NOT ONLY `overdue`: before this lane the sweep reported only
# overdue, so `overdue=0` was repeatedly recorded as "pipeline clean / stores
# healthy" while 27 eligible records sat unsurfaced (measured 2026-08-26).
# Primary source: all active hypotheses
Bash: pipeline-read.sh --stage active
# Also re-probe measurement-pending hypotheses (g-115-465 / rb-754) — these are
# shelved waiting for measurement infrastructure to appear. Re-checking the channel
# every cycle is cheap and lets them resolve as soon as data shows up. A re-probed
# measurement-pending record now past its hard resolves_by deadline with the channel
# STILL empty is EXPIRED by Step 2.6a (g-115-1584 / rb-2122) — without that pass the
# stage was a one-way shelf with no auto-expiry that grew unbounded (g-001-02 had to
# hand-archive 35 past-deadline records).
Bash: pipeline-read.sh --stage measurement-pending
APPEND to candidate list
# Horizon filter: micro-hypotheses never enter this pipeline.
# Session-horizon hypotheses use self-check verification (Step 2 handles this).
# Filter OUT any records with horizon: micro (shouldn't exist in pipeline, but defensive).
Filter out records where horizon == "micro"
Sort by resolves_no_earlier_than (soonest first), then end_date for legacy records
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.
- 4d ago Changed · +1 lines 1d84719cfe72
- 8d ago Changed · +5 lines 7ccd2f340224
- 12d ago First seen · 1,071 lines · 94 tokens per session scan A 99fb76f84628
review-hypotheses is a skill published in the GitHub repository zkysar1/Claude-Mind (5 stars, last pushed yesterday), licensed MIT. It adds 94 tokens to every session and 13,120 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 2026-08-31.
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