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/research-topic/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/research-topic)<a href="https://agentmods.dev/skills/zkysar1/claude-mind/research-topic"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/research-topic/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/research-topic"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/research-topic.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 | $0.00096 | $0.02915 |
| Opus 5 | $0.00048 | $0.01458 |
| Sonnet 5 | $0.00019 | $0.00583 |
| Haiku 4.5 | $0.00010 | $0.00292 |
Grade A, and why
research-topic 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 9d 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 — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/research-topic — Web Research Engine
Researches topics using WebSearch/WebFetch and writes findings directly to memory tree nodes. Called by /aspirations for knowledge goals, /reflect for gap-filling, and /replay for domain transfer.
Parameters
<topic>(required) — Topic to research--depth quick|standard|deep— Research intensity (default: standard)--target-node <key>— Tree node key to update (auto-detected if omitted)
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.
Step 1: Scope
Before any external research, determine what we already know and what gaps remain.
Bash: retrieve.sh --category {topic-category} --depth shallow
# Returns tree_nodes, experiences, reasoning_bank, guardrails, etc.
# Check if tree nodes already cover this topic (avoid redundant research)
# Check if experiences show prior research attempts
1. If target-node provided: use that node
Else: node=$(bash core/scripts/tree-find-node.sh --text "{topic}" --leaf-only --top 1)
# Returns: {key, score, file, depth, summary, node_type}
2. If matching node found (node.score > 0):
- Read its .md file
- Note what's already documented, identify gaps
- Research focus = gaps only (never re-research known content)
3. If no matching node found:
- Identify best parent for a new node (SPROUT)
- Compute path: bash core/scripts/tree-read.sh --child-path <parent> <topic-slug>
- Research focus = broad (building initial understanding)
Step 1.5: Encode-Stable-Facts Gate (G17)
Before external probing, check whether the topic names a resource whose locator
is already encoded in world/conventions/. This prevents redundant web discovery
for stable facts (paths, endpoints, account IDs) that prior sessions already found.
Bash: bash core/scripts/encode-stable-facts-gate.sh \
--resource-id "{topic}" \
--probe-count 0 \
--threshold 3
# Exit 0 → proceed to Step 2 (resource not yet at threshold, or locator already exists).
# Exit 1 → the topic names a resource that has been probed ≥3 times without encoding.
# Read the JSON output: if locator_found is true, read locator_file and use the
# encoded value instead of re-discovering via web search. If locator_found is false,
# proceed to Step 2 but encode any stable locator values discovered into
# world/conventions/ before returning (per .claude/rules/encode-stable-facts.md).
#
# Note: probe-count starts at 0 here (first invocation for this topic this session).
# Callers that invoke research-topic multiple times for the same resource should
# increment probe-count across calls. The --threshold 3 default applies; research-topic
# may use a higher threshold via --threshold if broad exploration is documented.
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.
- 9d ago First seen · 277 lines · 96 tokens per session scan A 0ecce8f2fd9d
research-topic is a skill published in the GitHub repository zkysar1/Claude-Mind (5 stars, last pushed yesterday), licensed MIT. It adds 96 tokens to every session and 2,915 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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