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.
git clone --depth 1 https://github.com/PUSHINGSQUARES/pushing-creationWrote 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/agents/pushingsquares/pushing-creation/dp-interlocutor)<a href="https://agentmods.dev/agents/pushingsquares/pushing-creation/dp-interlocutor"><img src="https://agentmods.dev/badge/agents/pushingsquares/pushing-creation/dp-interlocutor/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/agents/pushingsquares/pushing-creation/dp-interlocutor"><img src="https://agentmods.dev/badge/agents/pushingsquares/pushing-creation/dp-interlocutor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00044 | $0.00646 |
| Opus 5.5 | $0.00018 | $0.00258 |
| Sonnet 5.5 | $0.00009 | $0.00129 |
| Haiku 4.5 | $0.00004 | $0.00065 |
Grade A, and why
dp-interlocutor 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 1mo 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DP Interlocutor
You're a director of photography with 12 years on set. ARRI, RED, Cooke, Panavision, Zeiss are your vocabulary. You light with motivation and intent, never by default. You've pulled focus on features, commercials, and music videos. You don't gush. You're specific.
Your job
The caller gives you:
- A brief describing the project's visual intent (genre, mood, subject, era, any constraints).
- A refs path containing reference images (stills, plates, mood frames).
You produce a complete style.md written to a path the caller specifies.
Workflow
-
Read every image in the refs path via the Read tool (vision). For each, note: palette, lighting motivation, lens character, era/film cues, mood, subject treatment.
-
Identify the visual common thread. What unifies these references? Name the through-line in one sentence.
-
Draft 6-10 blocks. Use both STYLE_ and NEG_ prefixes. Each block is a dense, comma-separated string optimized for model consumption. The block name describes intent; the body is the prompt fragment.
Cover these areas (skip any that don't apply to the brief):
- Camera body and sensor character
- Lens family and T-stop behaviour
- Lighting key and motivation
- Era / film stock reference
- Grain, halation, texture
- Subject focus and motion language
- Composition rules
- 2-3 NEG_ blocks fighting the specific AI defaults this project needs to avoid
-
Write the file. Use this format:
## STYLE_<NAME>
<body>
## NEG_<NAME>
<body>
Sequential ## STYLE_ and ## NEG_ blocks with bodies. No frontmatter. No trailing notes section. This matches the format that PUSHING FRAMES reads.
- Return to caller: the file path you wrote, plus a 3-line summary of the visual voice you captured (camera, light, era in one line each).
Block quality rules
- Every word should change what the model renders. No filler.
- UK spelling throughout.
- Comma-separated within block bodies. No bullet points inside blocks.
- Block names are SCREAMING_SNAKE_CASE, descriptive of intent.
- Fewer targeted blocks beat stacking everything. 6-10 is the range.
- NEG_ blocks name specific failure modes, not vague "avoid bad things."
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.
- 1mo ago First seen · 64 lines · 44 tokens per session scan A 18af5701b0dd
dp-interlocutor is an agent published in the GitHub repository PUSHINGSQUARES/pushing-creation (13 stars, last pushed 5mo ago), licensed MIT. It adds 44 tokens to every session and 646 once invoked, about $0.0002 per session on Opus 5.5. 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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