Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders.

Apache-2.0Auto-check passedEducation

Install Synthesize

skills CLI
$ npx skills add agentii-ai/agentii-investment-intelligence --skill synthesize -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install agentii-ai/agentii-investment-intelligence synthesize --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/vertical-plugins/scenarios/skills/agentii/synthesize .claude/skills/synthesize && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
synthesize
GitHub stars
207
Token cost
~3.2k tokens
SKILL.md length
1,147 words
Files
2 (incl. references)
Skills in repo
79
Repo updated
First seen
Licence
Apache-2.0

At a glance

Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders.

  • Works in 6 steps: One or more … blocks, no nesting. The… → Fragment only — <!DOCTYPE>, , , , , → No and no id starting cover- or equal to… → …
  • Tasks that involve Essays and academic help
  • SKILL.md covers When to run, The loop (four steps + optimize), Deliverables and content.html contract (the…, plus 5 more sections
  • Calls python3

What it does

Synthesize is an agent skill from agentii-ai/agentii-investment-intelligence. Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders. Four-step loop — pack (deterministic Python bundle of all sources + report/metrics.json), author (the LLM writes report/content.html — narrative, KPI tiles, badges, timeline, tables and citations are LLM judgment), assemble (deterministic validation, template injection, Q50 pins, Q47 overflow gate), render + optimize (Chrome headless per-page PNGs — the LLM reads them…

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/modes.md`).

It sits in Education, covering Essays and academic help, OKRs and executive reporting and Citation management. It works with Python. The repository describes itself as: Claude-type skills for institutional equity research — 25 AI agent skills with SEC filings, XBRL financials, earnings calendars, DCF/comps/LBO models, and PPT generation. Powered… The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Essays and academic help
  • Tasks that involve OKRs and executive reporting
  • Tasks that involve Citation management

Example prompts

  • “/synthesize”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. One or more … blocks, no nesting. The cover
  2. Fragment only — <!DOCTYPE>, , , , ,
  3. No and no id starting cover- or equal to stale-bar`.
  4. Reserved classes — never emit these (assembler chrome)
  5. Citation gate (anti-fabrication): every viewer link you emit must be
  6. Charts (Q48) are tokens, not images

What it can do on your machine

Read from SKILL.md and the folder at commit 86980e1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Synthesize loads about 3.2k tokens when it runs, and up to ~3.3k if it reads all its reference files. Until then it costs about 149 tokens; SKILL.md has 1,147 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~149
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from agentii-ai/agentii-investment-intelligence at commit 86980e1, republished under its Apache-2.0 licence (© agentii-ai). 1,147 words, ~3,207 tokens.

Download SKILL.mdSave it as .claude/skills/synthesize/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
synthesize
description
Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders. Four-step loop — pack (deterministic Python bundle of all sources + report/metrics.json), author (the LLM writes report/content.html — narrative, KPI tiles, badges, timeline, tables and citations are LLM judgment), assemble (deterministic validation, template injection, Q50 pins, Q47 overflow gate), render + optimize (Chrome headless per-page PNGs — the LLM reads them and iterates until every page is visually clean). Spec 046 Q46–Q50.
role
kit
market_data_stage
none
retrieval_scope
structured_only

agentii.synthesize

The single-point HTML generation step (spec 046 Q46–Q50): ONE thesis-report.html per thesis, authored from the markdown artifacts and then optimized against real renders. Analysis skills emit markdown only (Q49); the report is assembled here, at the synthesis step, after the cross-stock synthesis (_cross/*_synthesis.md) exists.

When to run

  • After the synthesis tasks complete (the _cross/ deliverable is written).
  • When converge emits an html_stale finding (sources or template moved).
  • On explicit request, or once at thesis completion (Q50 regeneration triggers).

The loop (four steps + optimize)

bash
# 0. RESOLVE the kit root — contracts/kit-root.md. The kit's scripts do NOT ship with
#    the skills, so never assume the CWD is the checkout (`cd agentii-investment-
#    intelligence` was this skill's old step 0, and it only worked for a user sitting
#    in the checkout). This resolver fails loudly rather than guessing:
KIT=""
for c in "${AGENTII_KIT_ROOT:-}" \
         "$(cat "$HOME/.claude/skills/agentii/.kit-root" 2>/dev/null)" \
         "${CLAUDE_PLUGIN_ROOT:-}"; do
  [ -n "$c" ] && [ -f "$c/scripts/agentii_cmd.py" ] && { KIT="$c"; break; }
done
if [ -z "$KIT" ]; then d="$PWD"; while [ "$d" != "/" ]; do
  [ -f "$d/scripts/agentii_cmd.py" ] && { KIT="$d"; break; }; d="$(dirname "$d")"; done; fi
[ -n "$KIT" ] || { echo "agentii kit not found — see contracts/kit-root.md" >&2; exit 1; }

# 1. PACK — deterministic bundle of every source, verbatim (no timestamps),
#    PLUS report/metrics.json (per-ticker key_metrics/conclusions/counts —
#    machine-ready numbers for KPI tiles and kpi_trend charts, RAW values):
python3 "$KIT/scripts/synthesize_report.py" pack --thesis <theses/{nnn}-{slug}>

# 2. AUTHOR — read <thesis>/report-input.md (verbatim sources + citations)
#    and <thesis>/report/metrics.json (numbers). Write
#    <thesis>/report/content.html — the report's actual content is YOUR judgment.

# 2b. SCORE (required — spec 058 FR-065). The blocking gate decides what TEXT can
#     decide; it cannot see whether the report is any good, and "passes the gate"
#     must never be read as "reads well". Run the scorer for the RUBRIC and the
#     MEASURED evidence — the judgement is yours, the measurement is not:
python3 "$KIT/scripts/score_report_readability.py" <thesis-dir>/report/content.html
#     Then read the report and record your total (five criteria, 1–5 each → 1–25)
#     in <thesis-dir>/report/readability.json:
#       {"score": 21, "previous": 18, "explanation": ""}
#     `previous` is the last RELEASED report's score; omit it (or write null) for a
#     first report, which sets its own baseline — no score is chosen in advance.
#     A score BELOW `previous` requires `explanation`, and `assemble` REFUSES the
#     drop without one: FR-065's consequence is that a regression is explained in
#     the deliverable, and a score recorded without consequence is the defect
#     FR-040 forbids. A LOW score is not refused — only an unexplained regression.
#     The score is rendered on the cover beside the pins (T091), so it has a named
#     consumer: the human reviewer.

# 3. ASSEMBLE — validate + inject + gate (advisories on stderr are guidance,
#    the hard gates are silent until they fail):
python3 "$KIT/scripts/synthesize_report.py" assemble --thesis <thesis-dir> --check-only  # fit loop
python3 "$KIT/scripts/synthesize_report.py" assemble --thesis <thesis-dir>               # deliver

# 4. RENDER — Chrome headless → letter PDF → per-page PNGs + manifest.
#    --keep-pdf is REQUIRED for delivery: without it the PDF is written to a temp dir,
#    used for the PNGs, and DELETED. The deliverable is HTML **and** PDF.
python3 "$KIT/scripts/render_report.py" render --thesis <thesis-dir> --keep-pdf

# 5. OPTIMIZE (required, not optional): READ the PNGs page by page, in batches
#    of 3–4. Fix real problems the estimator cannot see — clipped tables, ugly
#    URL wrapping, weak density, orphan headings, oversized tiles. Edit
#    content.html → re-assemble → re-render until EVERY page is visually clean.

Deliverables

Two files, both at the thesis root — report the absolute paths when you finish:

  • <thesis-dir>/thesis-report.html
  • <thesis-dir>/thesis-report.pdf

The PDF is the deliverable, not a QA by-product. render's docstring frames it as the "visual QA loop" because the PNGs are what the optimize pass reads — but --keep-pdf is what turns its --print-to-pdf output into the artifact a user actually sends to someone, and it belongs beside the HTML rather than in the report/pages/ scratch folder with the PNGs.

Renders never gate CI (Chrome/poppler may be absent) — the author's own visual pass is the gate. assemble --check-only remains the estimator fallback; a missing render is a hard stop for delivery, not a silent skip. render --verify also checks each PNG is letter-width at the requested dpi.

content.html contract (the assembler hard-gates every rule)

You author only the page sequence — a fragment, never a document:

  1. One or more <section class="page">…</section> blocks, no nesting. The cover is page 1 and is template-owned: do not author it — the assembler fills kicker / title / claim / pins / universe / generated / TOC, and injects the running sheet head/foot, page marks (NN / TOTAL) and corner registration marks into every page.
  2. Fragment only — <!DOCTYPE>, <html>, <head>, <body>, <style>, <script> are rejected. Element whitelist: section h1 h2 h3 p ul ol li table thead tbody tr th td b strong i em code a div span br hr blockquote.
  3. No <img> and no id starting cover- or equal to stale-bar.
  4. Reserved classes — never emit these (assembler chrome): sheet-head, sheet-foot, reg, cover, page-mark, disclaimer. A collision is a hard validation error, not a warning. The disclaimer page is the newest of these (Q139): one legal tail page, numbered last, injected by synthesize_report.build_html from templates/disclaimer.md — the single source for that text. Do not author it, do not paraphrase it, and do not put a disclaimer in a page of your own. It is deliberately absent from the contents list: it is a legal tail, not a chapter.
  5. Citation gate (anti-fabrication): every viewer link you emit must be copied verbatim from report-input.md — the pack's links have the form …/v/{TICKER}/{citation_id}/{N} on the agentii viewer. The assembler rejects any {ticker}/{citation_id} pair it cannot find in the sources, with an offender list. Never invent a citation_id; every [FACT] number you surface keeps its citation link. metrics.json carries NO citation ids — never build viewer links from tiles. Citations that only exist as bare text in the pack (keyword scans like ISRG × ect75 × page1) may be rendered as plain text — do not turn them into fake links.
  6. Charts (Q48) are tokens, not images:
    html
    <div data-chart="kpi_trend" data-spec='{"x":["FY2024","FY2025","H1 2026"],"y":[77.7,128.3,96.3]}' data-height="160"></div>
    data-spec is single-quoted JSON (no apostrophes inside). kpi_trend is for non-price structured series (capex trajectories, revenue series) built from metrics.json multi-period keys. football_field {labels,lows,highs}, peer_bars {labels,values}, scatter {x,y}, scenario_tree {edges} remain market-data-only. data-height is your page-budget claim — the overflow estimator counts it exactly, so keep it honest. Research-only theses (market-data stage none) emit only kpi_trend, if anything.

Component rules (v0.3.0 design system)

  • KPI tiles: the executive-summary page REQUIRED to open with a .stat-row of 2–4 thesis-level tiles (e.g. artifacts count · key-metrics count · pillars supported · GPT-3.5 window). Per-ticker sections carry 2–4 ticker tiles. Structure: div.stat > div.num + div.lbl + div.sub. Numbers from metrics.json, formatted per style.md: $28.5B (not $28,476M; one decimal for billions, none for millions), 12.4%, +12.4%, 14.2x.
  • Badges — two orthogonal axes, never confused:
    • taxonomy (FR-092): [FACT]→.badge-fact, [DEDUCTED]→.badge-deducted, [VIEW]→.badge-view — use on evidence-table rows and claim prose;
    • verdicts: supported→.badge-supported, indeterminate→ .badge-indeterminate, refuted→.badge-refuted — every pillar verdict carries one.
  • Timeline: the capability-timeline page uses .timeline with .tl-item blocks — .tl-phase holds the mono phase label, the prose keeps the synthesis's wording with its citations.
  • Kickers: every page opens with a .sec-kicker (mono editorial label, e.g. THE CORPUS · 24 ARTIFACTS), never the heading text repeated.
Show full SKILL.md (447 more words)Show less

Letter-fit rules (author to these numbers)

A letter page holds ~40 lines of prose at 11pt — the --check-only gate, the render PNGs and the in-browser red ⚠ overflow outline are the enforcement. Author conservatively:

  • ≤ 40 prose lines per page (paragraphs + bullets, combined).
  • ≤ 18 table rows per page when cells wrap ≤ 2 lines each; a citation cell counts as 2 lines. Split long tables across pages by ticker or period.
  • A .stat-row costs ~4 lines; a .tl-item costs ~3; a chart token costs its data-height honestly.
  • Headings cost budget: one h1/h2 + 2–3 short paragraphs, or a table block — not both, unless the table is small.

What a good report contains

  • Executive Summary — the synthesis's own prose, condensed to the operative sentences; tile row; the headline callout (capability timeline band + confidence) kept intact; verdict list with badges.
  • Pillar verdicts — every pillar: verdict badge, falsifier result, the best evidence bullets with citations (verbatim from the pack).
  • Capability timeline — the synthesis §2 content as a styled .timeline (it is the thesis's headline output).
  • Evidence — the cross-ticker table (§3) split to fit, [FACT] badges on rows, citation links inline; negative findings ("no MTBF disclosure anywhere") are evidence too — keep them.
  • Coverage gaps — the synthesis §4 items; the mechanical rollup (entry counts by skill) may appear as one small table.
  • Data-quality flags (§5) and contract compliance (§6), condensed.
  • Nothing from the raw YAML/JSON of sources — the pack and metrics.json are your inputs, not your output; prose and structure are yours, facts and citations are verbatim.

Quality checklist (MUST, before delivery)

  1. Exec-summary tile row present (2–4 tiles).
  2. All pillar verdicts carry colored badges; taxonomy badges on evidence rows.
  3. Capability timeline styled (.timeline/.tl-item/.tl-phase).
  4. Evidence tables follow style.md (Metric → Current → Prior → YoY → Citation) with inline citation links on every fact.
  5. .sec-kicker on every page.
  6. No empty pages, no orphan headings at page bottoms.
  7. No raw markdown leakage (**, backtick fences, ### ).
  8. Tier-0 --check-only pass AND render page-count == section-count AND every PNG visually verified clean (no clipped tables, no red overflow outlines, sane density).
  9. Readability scored (FR-065). report/readability.json carries the 1–25 total from score_report_readability.py, and a score below the previous release's carries an explanation. assemble refuses a drop without one, so a missing explanation is a hard stop, not a note. The score appears on the cover beside the pins and is the ONLY readability signal a reader sees — the blocking gate's pass is not a substitute, and the two are deliberately reported separately so neither can be mistaken for the other.

Regeneration discipline (Q50)

The assembled report embeds sources_hash (all markdown sources) + template_version; converge flags html_stale when they drift. Re-run the loop above when that finding appears — never hand-edit thesis-report.html.

© agentii-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in plugins/vertical-plugins/scenarios/skills/agentii/synthesize of agentii-ai/agentii-investment-intelligence.

  • SKILL.md
  • references/modes.md

Open the folder on GitHubat commit 86980e1

Compare with similar skills

Synthesize next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Synthesize compared with similar skills
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Latex Thesis Zhbrycewang-stanford/Auto-Empirical-Research-Skills4.6k—~1.5kAutomated safety check: PassCustom licence
Modeling Paper Rubric and Model Selectoryushui2022/MathModel-Skill4541 repos~1.8kAutomated safety check: PassMIT
Autonomous Researchfedericodeponte/opendraft507—~8.2kAutomated safety check: PassApache-2.0
Aigc Detectorfree-revalution/AIGC-Detector-Pro142—~2.8kAutomated safety check: PassMIT

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Works with

Questions about Synthesize

What does Synthesize do?

Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders. Synthesize is an agent skill from agentii-ai/agentii-investment-intelligence.html, then OPTIMIZE it against real page renders.

When should I use Synthesize?

Synthesize fits situations like: tasks that involve Essays and academic help; tasks that involve OKRs and executive reporting; tasks that involve Citation management.

How do I install Synthesize in Claude Code?

Run `npx skills add agentii-ai/agentii-investment-intelligence --skill synthesize -a claude-code`. Or copy the skill folder (plugins/vertical-plugins/scenarios/skills/agentii/synthesize in agentii-ai/agentii-investment-intelligence) into .claude/skills/synthesize in your project. Claude Code loads it when a task matches its description.

How do I install Synthesize in Codex?

Run `npx skills add agentii-ai/agentii-investment-intelligence --skill synthesize -a codex`. Or copy the skill folder (plugins/vertical-plugins/scenarios/skills/agentii/synthesize in agentii-ai/agentii-investment-intelligence) into .agents/skills/synthesize in your project. Codex loads it when a task matches its description.

Can I use Synthesize in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add agentii-ai/agentii-investment-intelligence --skill synthesize -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/synthesize, .gemini/skills/synthesize, .github/skills/synthesize and .opencode/skills/synthesize in your project.

What does Synthesize need to run?

Going by SKILL.md and its folder, Synthesize needs the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Synthesize access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Synthesize safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Synthesize use?

Synthesize is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Synthesize use?

About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 137 tokens, read only when the agent opens those files.

What are the alternatives to Synthesize?

Skills that share tags, products or a category with Synthesize: Thesis Creator (Stars-OC/thesis-creator, 230 stars), Latex Thesis Zh (brycewang-stanford/Auto-Empirical-Research-Skills, 4.6k stars), Modeling Paper Rubric and Model Selector (yushui2022/MathModel-Skill, 454 stars) and Autonomous Research (federicodeponte/opendraft, 507 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Synthesize?

agentii-ai (a GitHub user) maintains it in agentii-ai/agentii-investment-intelligence, which has 207 GitHub stars. The repository holds 79 skills in this directory. The repository was last updated on September 29, 2026.

Source: agentii-ai/agentii-investment-intelligence on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.