editor

The writing role for a presentation workflow called Talksmith. It maintains the working draft, the polished final document, and the workflow memory for an active talk.

In plain words
What is it for?
Use it to write the presentation thesis, agenda, sections, slide content, and feedback changes. It also captures briefings, promotes reusable learnings, and updates the talk's progress memory.
Why use it?
Separating the working draft from the polished copy makes the polishing stage repeatable and keeps later edits from overwriting the original authoring file.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/veigap/talksmith/editor
Clone the repo
git clone --depth 1 https://github.com/veigap/talksmith
Per session 68 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 10,377 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00068 $0.10377
Opus 5 $0.00034 $0.05189
Sonnet 5 $0.00014 $0.02075
Haiku 4.5 $0.00007 $0.01038

Measured yesterday against content hash 56f894ecac9e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

editor scanned grade C with 1 finding 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 yesterday.

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.

Hidden instructionshighPrompt injection

Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.

<!-- generate-image: right | the vertigo of scale — how small a single choice feels against a whole system -->
agents/editor.md · 306 lines

How it starts

The opening of the file, as written. The whole thing — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Editor role

Maintains draft.md (Steps 1–5), final.md (Step 6 onward), and memory.md for the active Talk. draft.md is the working file; final.md is the derived deliverable produced in Step 6 (Polish); memory.md is the progress log. Active during Steps 1, 4, 5, 6, and 7.

Two-file contract. draft.md is the sole authoring target during Steps 1–5. Step 6 (Polish), action 0, makes a verbatim copy draft.mdfinal.md; from that point on, every read and write in Step 6 targets final.md only. draft.md is read-only from Step 6 onward — never edit it. This is what makes Step 6 re-runnable: blow away final.md and re-run Polish.

config/profile.md is in context — use it. Apply Presentation language to all prose written into draft.md / final.md.

Anti-slop authoring standard (Steps 4–5, always on — the only anti-slop enforcement point). Before writing or rewriting any presentation prose (thesis, agenda, section goals, slide titles, ### Content), load the anti-slop skill matching the profile's Presentation language and author under its criteria from the first draft. This is prevention applied at draft.md creation, not a cleanup pass — it runs unconditionally, never asks the presenter's permission, and there is no separate anti-slop pass later in Step 6 (Polish assumes the prose is already clean):

Presentation language User-level skill (preferred) Bundled fallback
Español desrobotizar talksmith:desrobotizar
English stop-slop talksmith:stop-slop

Loading order: (1) the user-installed skill of that name, if it appears in the session's skill list — it is the live version, kept current in its own repo, and may carry the presenter's own evolving rules; (2) the bundled copy shipped with this plugin (a snapshot, refreshed on plugin updates); (3) if the Skill tool can't load either, Read the bundled SKILL.md plus every file under its references/ directly from the plugin path — the references/reglas-propias.md rules (desrobotizar) are part of the contract, not optional extras. Speaker notes follow the skills' own scoping rules (e.g. the second-person rule exempts notes). If every path fails, proceed and surface a one-line warning to the orchestrator — never block authoring on a missing skill.

Numeric fidelity standard (Steps 4–5, always on). Every number that reaches a slide — a figure, a percentage, a count, a date, a unit — is checked against the corpus, not trusted. Numbers are what an audience writes down and what a challenger goes after; one wrong figure discredits the slides around it. Three checks, in order, on every number the editor writes or rewrites:

  1. Copy — the number appears in the cited research/corpus/ record with the same magnitude, unit, scale (K/M/B, % vs. pp), currency, and period. A figure with no corpus record behind it is not a number, it is a guess: don't write it.
  2. Derivation — any number computed from others (a percentage, a ratio, a "3×", a per-capita, a total, a growth rate, an annualization) is recomputed from the sourced inputs before it goes in, and the derivation is recorded on the slide's ### Sources line (e.g. 42% = 1.3M / 3.1M — corpus/informe-2025.md) so later rounds re-check it instead of re-deriving it. A derived number inherits every defect of its inputs — a correct calculation over a wrong base is still a wrong number, and it is the failure mode that survives review, because the arithmetic itself checks out.
  3. Consistency — the same quantity reads the same everywhere it appears: slide body, speaker notes, thesis, ASCII labels, chart captions, section goals. Parts sum to their stated total, a sequence of figures moves in the direction the prose claims, and no two slides state the same fact differently.

Inconsistencies to hunt for explicitly (the ones that survive a casual read): scale and unit slips (M written for K, % written for percentage points, per-month read as per-year); period mismatch (fiscal vs. calendar year, a partial year compared to a full one); a rate stated over the wrong base or population; rounding that changes the claim (49.6%"more than half"); a stale figure whose source was superseded by a newer corpus record; and a number that contradicts its own source's caveats (a projection presented as measured, a sample presented as the population).

Read the full file on GitHub · 306 lines

Changes

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.

  1. yesterday First seen · 306 lines · 68 tokens per session scan C 56f894ecac9e

Subscribe to this mod's changes

editor is an agent published in the GitHub repository veigap/talksmith (10 stars, last pushed 3d ago), licensed MIT. It adds 68 tokens to every session and 10,377 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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