/ase-meta-quotes

name: ase-meta-quotes
argument-hint: "[--help|-h] [--ground|-g] [--proximity|-p] [--count|-c <count>] <topic-keywords>"
description: >
    Find quotes for a set of topic keywords and place them into a
    2x2 matrix, spanned by the presence of an author/origin and by
    the literal containment of a keyword, optionally grounded in
    Internet/Web facts and optionally widened to the conceptual
    neighborhood of the topic. Use when the user wants "quotes",
    "sayings", "aphorisms", or "citations" on a topic.
user-invocable: true
disable-model-invocation: false
effort: high
allowed-tools:
    - "Agent"

@${CLAUDE_SKILL_DIR}/../../meta/ase-control.md @${CLAUDE_SKILL_DIR}/../../meta/ase-skill.md @${CLAUDE_SKILL_DIR}/../../meta/ase-getopt.md

<purpose name="ase-meta-quotes"> Find Quotes on a Topic </purpose>

<expand name="getopt" arg1="ase-meta-quotes" arg2="--ground|-g --proximity|-p --count|-c=8"> $ARGUMENTS </expand>

<objective> *Find* quotes for the following topic keywords: <keywords><getopt-arguments/></keywords> </objective>

<flow>

1. <step id="STEP 1: Sanity Check Usage">

1. <if condition="<keywords/> is empty"> Only output the following <template/> and then immediately *STOP* processing the entire current skill:

<template> ⧉ **ASE**: ✪ skill: **ase-meta-quotes**, ▶ ERROR: expected a `<topic-keywords>` argument </template> </if>

2. Set <quotes></quotes> (set to empty).

3. Determine the maximum total number of *quotes* to surface: set <count/> to <getopt-option-count/>; if <getopt-option-count/> is *non-numeric* or *less than or equal to 0*, use the default *8* instead.

</step>

2. <step id="STEP 2: Harvest Quotes">

1. Determine *quotes* -- sayings, aphorisms, maxims, proverbs, and citations -- which are about the topic <keywords/>, and store them in <quotes/>. Per quote, record its *text*, its *author* (a named person or organization, if any is known), its *origin* (a named work, standard, or document, if any is known), and <keywords/> as its *source topic*.

2. <if condition="<getopt-option-ground/> is equal `true`">

*Additionally* -- and never *instead* -- gather quotes from the Internet/Web by using the `ase-meta-search` skill in a sub-agent with the following tool call:

`Agent( description: "Query Web Search Service", subagent_type: "ase:ase-meta-search", prompt: "Search the Internet/Web and gather quotes about the following topic: <keywords/>", run_in_background: false )`

Merge the returned quotes into <quotes/>, deduplicating quotes which differ only in punctuation, capitalization, or attribution wording, and remember for every quote whether the search *confirmed* its exact wording and attribution.

<if condition="the sub-agent returned no usable quotes"> Output the following <template/> and continue with the model knowledge only:

<template> <ase-tpl-bullet-secondary/> **WARNING**: grounding found no usable quotes -- falling back to model knowledge. </template> </if>

</if>

</step>

3. <step id="STEP 3: Widen Topic via Proximity" condition="<getopt-option-proximity/> is equal `true`">

1. Set <prompt><keywords/></prompt>.

2. <if condition="<getopt-option-ground/> is equal `true`"> Set <prompt>GROUND <keywords/></prompt>, so the agent grounds its determination in Internet/Web facts instead of using model knowledge only. </if>

3. Determine the *conceptual neighborhood* of <keywords/> by using the `ase-meta-proximity` agent in a sub-agent with the following tool call:

`Agent( description: "Determine Conceptual Proximity", subagent_type: "ase:ase-meta-proximity", prompt: "<prompt/>", run_in_background: false )`

4. <if condition="the sub-agent returned no usable neighborhood"> Output the following <template/>, *SKIP* the remaining sub-steps of this step, and continue with the quotes harvested in STEP 2 only:

<template> <ase-tpl-bullet-secondary/> **WARNING**: proximity agent returned no usable result -- keeping the narrow topic only. </template> </if>

5. Parse the returned labeled list and set <neighborhood/> to the values of its `PARENT:` line (the *broader* topic), of its four `SIBLING:` lines (the *same-level* topics), and of its four `CHILD:` lines (the *narrower* topics).

6. Harvest quotes for *each* topic of <neighborhood/> exactly as in STEP 2 (Harvest Quotes), record the contributing neighborhood topic as the *source topic* of each of those quotes, and merge the results into <quotes/>.

</step>

4. <step id="STEP 4: Classify and Render Quotes">

1. *Classify Quotes*:

Classify every quote of <quotes/> along two *orthogonal* axes:

• **ATTRIBUTION**:

A quote is `ATTRIBUTED` if a named *author* and/or a named *origin* is known for it, and `ANONYMOUS` otherwise.

• **LITERALNESS**:

A quote is `LITERAL` if its text contains at least one of the topic keywords of <keywords/> as a *whole word* -- matched *case-insensitively* and tolerating *inflections* (e.g. `architect` and `architectural` match the keyword `architecture`), but *never* as a mere *substring* (e.g. `art` does *not* match `architecture`). A quote is `THEMATIC` otherwise.

Both axes span the four *quadrants*:

• `Q1` (`ATTRIBUTED` and `LITERAL`)
• `Q2` (`ATTRIBUTED` and `THEMATIC`)
• `Q3` (`ANONYMOUS` and `LITERAL`)

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