majiayu000/ase-meta-quotes

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

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

<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>

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

1. 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>

1. <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.

1. <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>

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

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

1. <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>

1. 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 )

1. <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>

1. 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).

1. 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>

1. <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)
• Q4 (ANONYMOUS and THEMATIC)

1. Finally, reduce <quotes/> to at most <count/> quotes in total,

distributed as evenly as possible across the four quadrants and preferring the most relevant and most well-known quote per quadrant.

1. Render Quotes:

Render every quote on its own ○-prefixed line, with the following suffixes appended in this order:

• — *<author/>*, <origin/> in the two ATTRIBUTED quadrants,

omitting whichever of <author/> and <origin/> is unknown.

• [from proximity: <source-topic/>] if the quote was

harvested for a neighborhood topic in STEP 3 rather than for <keywords/> itself.

• *(unverified)* if the exact wording or the attribution of

the quote could not be established with confidence -- but omit this marker for a quote whose wording and attribution the Internet/Web search of STEP 2.2 confirmed -- including its re-application for a neighborhood topic in STEP 3.

Render the single line ○ (none) for a quadrant without any quote. Output the result with the following <template/>:

<template> <ase-tpl-head title="QUOTES"/>

● Q1 - ATTRIBUTED / LITERAL: ○ ...]

● Q2 - ATTRIBUTED / THEMATIC: ○ ...]

● Q3 - ANONYMOUS / LITERAL: ○ ...]

● Q4 - ANONYMOUS / THEMATIC: ○ ...]

<ase-tpl-foot title="QUOTES"/> </template>

</step>

</flow>